Sorting spikes from extracellular recording into clusters associated with distinct single units (putative neurons) is a fundamental step in analyzing neuronal populations. Such spike sorting is intrinsically unsupervised, as the number of neurons are not known a priori. Therefor, any spike sorting is an unsupervised learning problem that requires either of the two approaches: specification of a fixed value k for the number of clusters to seek, or generation of candidate partitions for several possible values of c, followed by selection of a best candidate based on various post-clustering validation criteria. In this paper, we investigate the first approach and evaluate the utility of several methods for providing lower dimensional visualization of the cluster structure and on subsequent spike clustering. We also introduce a visualization technique called improved visual assessment of cluster tendency (iVAT) to estimate possible cluster structures in data without the need for dimensionality reduction. Experimental results are conducted on two datasets with ground truth labels. In data with a relatively small number of clusters, iVAT is beneficial in estimating the number of clusters to inform the initialization of clustering algorithms. With larger numbers of clusters, iVAT gives a useful estimate of the coarse cluster structure but sometimes fails to indicate the presumptive number of clusters. We show that noise associated with recording extracellular neuronal potentials can disrupt computational clustering schemes, highlighting the benefit of probabilistic clustering models. Our results show that t-Distributed Stochastic Neighbor Embedding (t-SNE) provides representations of the data that yield more accurate visualization of potential cluster structure to inform the clustering stage. Moreover, The clusters obtained using t-SNE features were more reliable than the clusters obtained using the other methods, which indicates that t-SNE can potentially be used for both visualization and to extract features to be used by any clustering algorithm.

Clustering Illusion is a cognitive bias and defined as the tendency to see patterns where no patterns exist (Gilovich, 1991; Gilovich, Vallone, & Tversky, 1985). This tendency can be observed when people interpret patterns or trends in random distributions. In the context of the VALCRI (Visual Analytics for Sense-making in CRiminal Intelligence analysis) project eight cognitive biases have been identified which may influence the decision-making process of the analysts. Assessment methods for other cognitive biases exist but this is not the case for the clustering illusion. Based on the study of Cook and Smallman (2007), who studied how cognitive biases affect a JIGSAW "Joint Intelligence Graphical Situation Awareness Web" system, a task that enables to detect the clustering illusion in a visual analytics environment was created. This task was as follows: Participants interacted with a selected set of tools from a visual analytics environment. These tools showed the spatial and chronological distribution of crime incidents in two city districts of Birmingham. In each city district, there were 30 crime incidents. A 2x2 design of random vs. pattern condition and interactive vs static condition was used to detect the influence of patterns and the level of interaction on the decision-making of the participants: In the random condition, the crime incidents have been randomly selected from a large set of incidents. In the pattern condition, the incidents have been selected in a way that there are increases or decreases over time and a spatial concentration of incidents in one of the two city districts. In the interactive condition, participants were allowed to interact with the tools to inspect the incidents from different perspectives. In the static condition, participants were asked to inspect the incidents as shown on the screen without interacting with the tools. After inspecting the incidents for ten minutes, the participants were asked (i) to evaluate if they would increase police presence either in city district A or in city district B, (ii) to evaluate the certainty of their decision, (iii) to announce if their decision was based on the data or patterns and trends in the data and if yes (iv) if they could argue their decision. The univariate analysis of variance showed no significant difference between the random and pattern conditions nor between the interactive and static condition and no interactions. A significant correlation between certainty of the decision and justifying the decision with facts (r=.364, p <.001) was found.

Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996). Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999). Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential. Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012). Slip and dilation tendency for the Tuscarora geothermal field was calculated based on the faults mapped Tuscarora area (Dering, 2013). The Tuscarora area lies in the Basin and Range Province, as such we applied a normal faulting stress regime to the Tuscarora area faults, with a minimum horizontal stress direction oriented 115, based on inspection of local and regional stress determinations, as explained above. Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60 degrees dipping fault segments have the highest tendency to slip. Tuscarora is defined by a left-step in a major north- to-north northeast striking, west-dipping range-bounding normal fault system. Faults within the broad step define an anticlinal accommodation zone wherein east-dipping faults mainly occupy western half of the accommodation zone and west-dipping faults lie in the eastern half of the accommodation zone. The geothermal system resides in the axial part of the accommodation, straddling the two fault dip domains. Within the axial part of the accommodation zone several west-dipping, north northeast-striking faults are well oriented for both slip and dilation, including fault strands that are exploited for both production and injection for the Tuscarora geothermal power plant. NOTE: 'o' is used in this description to represent lowercase sigma.

Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996). Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999). Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential. Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012). Slip and dilation tendency for the San Emidio geothermal field was calculated based on the faults mapped Tuscarora area (Rhodes, 2011). The San Emidio area lies in the Basin and Range Province, as such we applied a normal faulting stress regime to the San Emidio area faults, with a minimum horizontal stress direction oriented 115, based on inspection of local and regional stress determinations, as explained above. This is consistent with the shmin determined through inversion of fault data by Rhodes (2011). Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60 degrees dipping fault segments have the highest tendency to slip. Interesting, the San Emidio geothermal field lies in an area of primarily north striking faults, which have moderate dilation tendency and moderate to low slip tendency. NOTE: 'o' is used in this description to represent lowercase sigma.

Slip and Dilation Tendency in focus areas Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996).

Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999).

Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential.

Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012).

Slip and dilation tendency for the McGinness Hills geothermal field was calculated based on the faults mapped McGinness Hills area (Siler 2012, unpublished). The McGinness Hills area lies in the Basin and Range Province, as such we applied a normal faulting stress regime to the McGinness area faults, with a minimum horizontal stress direction oriented 115, based on inspection of local and regional stress determinations, as explained above. Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60 degrees dipping fault segments have the highest tendency to slip. The McGinness Hills geothermal system is characterized by a left-step in a north-northeast striking west-dipping fault system within a north northeast striking accommodation zone. As such, the normal faults that define these two structures are well oriented for both slip and dilation, including the west dipping faults that are exploited for both production and injection. Interestingly, although there is pressure communication between production and injection wells at McGinness Hills (B. Delwiche, personal comm.) the northwest striking fault, which creates hard linkage between the production and injection locations, is poorly oriented for both slip and dilation and therefore unlikely to host permeability.

NOTE: 'o' is used in this description to represent lowercase sigma.

Slip and Dilation Tendency in focus areas Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996). Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999). Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential. Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012). Based on inversion of fault kinematic data, Edwards (2013) interpreted that two discrete stress orientations are preserved at Neal Hot Springs. An older episode of east-west directed extension and a younger episode of southwest-northeast directed sinistral, oblique -normal extension. This interpretation is consistent with the evolution of Cenozoic tectonics in the region (Edwards, 2013). As such we applied a southwest-northeast (060) directed normal faulting stress regime, consistent with the younger extensional episode, to the Neal Hot Springs faults. Under these stress conditions northeast striking steeply dipping fault segments have the highest tendency to dilate and northeast striking 60 degrees dipping fault segments have the highest tendency to slip. Under these stress conditions, both the Neal Fault and Sugarloaf Butte faults area well-oriented for both slip and dilation and thus for fracture permeability. In addition, several subsidiary faults on the eastern side and within the step-over between the Neal fault and Sugarloaf Butte fault are well oriented for slip and dilation as well. NOTE: 'o' is used in this description to represent lowercase sigma.

Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996).

Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999).

Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential.

Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012).

Slip and dilation tendency for the Salt Wells geothermal field was calculated based on the faults mapped in the Bunejug Mountains quadrangle (Hinz et al., 2011). The Salt Wells area lies in the Basin and Range Province (N. Hinz personal comm.) As such we applied a normal faulting stress regime to the Salt Wells area faults, with a minimum horizontal stress direction oriented 105, based on inspection of local and regional stress determinations. Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60 degrees dipping fault segments have the highest tendency to slip. Several such faults intersect in high density in the core of the accommodation zone in the Bunejug Mountains and local to the Salt Wells geothermal .

Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) provides an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = T / on (Morris et al., 1996).

Dilation tendency is defined by the stress acting normal to a given surface: Td = (o1-on) / (o1-o3) (Ferrill et al., 1999).

Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. Values range from a maximum of 1, a fault plane ideally oriented to slip or dilate under ambient stress conditions to zero, a fault plane with no potential to slip or dilate. Slip and dilation tendency values were calculated for each fault in the focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. The resulting along-fault and fault-to-fault variation in slip or dilation potential is a proxy for along fault and fault-to-fault variation in fluid flow conduit potential.

Stress Magnitudes and directions Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005) as well as local stress information if applicable. For faults within these focus systems we applied either a normal faulting stress regime where the vertical stress (sv) is larger than the maximum horizontal stress (shmax) which is larger than the minimum horizontal stress (sv>shmax>shmin) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. Based on visual inspection of the limited stress magnitude data in the Great Basin we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012).

Slip and dilation tendency analysis for the Patua geothermal system was calculated based on faults mapped in the Hazen Quadrangle (Faulds et al., 2011). Patua lies near the margin between the Basin and Range province, which is characterized by west-northwest directed extension and the Walker Lane province, characterized by west-northwest directed dextral shear. As such, the Patua area likely has been affected by tectonic stress associated with either or both of stress regimes over geologic time. In order to characterize this stress variation we calculated slip tendency at Patua for both normal faulting and strike slip faulting stress regimes. Based on examination of regional and local stress data (as explained above) we applied at shmin direction of 105 to Patua. Whether the vertical stress (sv) magnitude is larger than the maximum horizontal stress (shmax) a normal faulting stress regime or the maximum horizontal stress (shmax) magnitude is larger than the vertical stress (sv), a strike-slip faulting stress regime, has very little effect on the dilation tendency, which is controlled by the stresses acting normal to fault planes. As such the dilation tendency results for a strike-slip faulting stress regime and for a normal faulting stress regime are virtually identical, so we present one result for dilation tendency applicable to both strike-slip and normal faulting stress conditions along with slip tendency for both a normal faulting and a strike-slip faulting stress regime. Under these stress conditions, north-northeast striking steeply dipping fault segments have the highest dilation tendency. Under the strike-slip faulting stress regime, north-northwest and east-northeast striking, steeply dipping fault have the highest slip tendency, while under normal faulting conditions north northeast striking, 60 degrees dipping faults have the highest slip tendency.

NOTE: 'o' is used in this description to represent lowercase sigma.

We propose a deep learning-based method for detecting Socially Desirable Responding (SDR)—the tendency for individuals to distort questionnaire responses to present themselves in a favorable light. Our objective is to showcase that such novel methods can be leveraged to design instruments that have the potential to measure this construct in an effective way. Participants’ tendency to engage in SDR was initially modelled by specifying a latent variable model from Big Five personality scores, using data from 91 participants in a job application simulation (Big Five questionnaire and video introduction). Nonverbal visual cues (5,460 data points following data augmentation) were extracted from the participants’ video presentations in form of sequences of images for training a transfer learning model designated as Entrans. The objective of Entrans is to discern patterns within these cues in order to detect whether sample participants manifest higher or lower SDR tendency. We conducted a regression-based prediction task to train and evaluate Entrans, resulting in a promising performance (MSE = .07, RMSE = .27, ρ = .27). A further analysis was conducted using a classification-based prediction task, which corroborated the potential of Entrans as a tool for detecting SDR (AUC = .71). These results were further analyzed by a Grad-CAM method to elucidate the underlying model behaviors. Findings suggest that the middle and lower parts of the face were the regions relied upon by Entrans to identify individuals with higher tendency of SDR in the classification task. These tentative interpretations give rise to the suggestion that socially desirable responding in a questionnaire and impression management in a job interview might share a common underlying cause. While the detection of SDR during personnel selection presents a significant challenge for organizations, our proof-of-concept demonstrates how machine learning might be leveraged to develop practical solutions as well as addressing theoretical questions.

We propose a deep learning-based method for detecting Socially Desirable Responding (SDR)—the tendency for individuals to distort questionnaire responses to present themselves in a favorable light. Our objective is to showcase that such novel methods can be leveraged to design instruments that have the potential to measure this construct in an effective way. Participants’ tendency to engage in SDR was initially modelled by specifying a latent variable model from Big Five personality scores, using data from 91 participants in a job application simulation (Big Five questionnaire and video introduction). Nonverbal visual cues (5,460 data points following data augmentation) were extracted from the participants’ video presentations in form of sequences of images for training a transfer learning model designated as Entrans. The objective of Entrans is to discern patterns within these cues in order to detect whether sample participants manifest higher or lower SDR tendency. We conducted a regression-based prediction task to train and evaluate Entrans, resulting in a promising performance (MSE = .07, RMSE = .27, ρ = .27). A further analysis was conducted using a classification-based prediction task, which corroborated the potential of Entrans as a tool for detecting SDR (AUC = .71). These results were further analyzed by a Grad-CAM method to elucidate the underlying model behaviors. Findings suggest that the middle and lower parts of the face were the regions relied upon by Entrans to identify individuals with higher tendency of SDR in the classification task. These tentative interpretations give rise to the suggestion that socially desirable responding in a questionnaire and impression management in a job interview might share a common underlying cause. While the detection of SDR during personnel selection presents a significant challenge for organizations, our proof-of-concept demonstrates how machine learning might be leveraged to develop practical solutions as well as addressing theoretical questions.