https://github.com/MIT-LCP/license-and-dua/tree/master/draftshttps://github.com/MIT-LCP/license-and-dua/tree/master/drafts
Electronic Health Records (EHRs) are integral for storing comprehensive patient medical records, combining structured data (e.g., medications) with detailed clinical notes (e.g., physician notes). These elements are essential for straightforward data retrieval and provide deep, contextual insights into patient care. However, they often suffer from discrepancies due to unintuitive EHR system designs and human errors, posing serious risks to patient safety. To address this, we developed EHRCon, a new dataset and task specifically designed to ensure data consistency between structured tables and unstructured notes in EHRs. EHRCon was crafted in collaboration with healthcare professionals using the MIMIC-III EHR dataset, and includes manual annotations of 4,101 entities across 105 clinical notes checked against database entries for consistency. EHRCon has two versions, one using the original MIMIC-III schema, and another using the OMOP CDM schema, in order to increase its applicability and generalizability.
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Checking table of model precision.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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This Statistical First Release (SFR) provides revised information on the overall achievements of young people in GCE and Applied GCE examinations and other equivalent qualifications in 2009/10. This updates the provisional SFR released in October 2010 and contains revised national level analyses by school type, gender and subject and revised local authority level analyses by gender. Further tables are provided separately on the DfE statistics website only, including alternative local analyses, time series giving achievements in GCE A/AS level subjects, and achievements in GCE A level subjects by institution type and Local Authority.
The information in this SFR is based on data collated for the 2010 School and College (Key Stage 5) Performance Tables (formerly Achievement and Attainment Tables), which has now been checked by schools, and covers achievements in all Level 3 qualifications approved under Section 96 of the Learning and Skills Act (2000). The Qualifications and Curriculum Development Agency (QCDA) tariff is used to calculate point scores for all Level 3 qualifications.
Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
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To check how the table/chart preview works on the magda side
Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
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Statistics illustrates consumption, production, prices, and trade of Instruments and Apparatus for Measuring or Checking The Flow or Level of Liquids in Cote d'Ivoire from 2007 to 2024.
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China Export: HS 8: Drafting Tables and Machines, Whether or Not Automatic data was reported at 18.325 RMB mn in Dec 2024. This records a decrease from the previous number of 21.417 RMB mn for Nov 2024. China Export: HS 8: Drafting Tables and Machines, Whether or Not Automatic data is updated monthly, averaging 7.498 RMB mn from Jan 2015 (Median) to Dec 2024, with 120 observations. The data reached an all-time high of 21.417 RMB mn in Nov 2024 and a record low of 2.543 RMB mn in Feb 2020. China Export: HS 8: Drafting Tables and Machines, Whether or Not Automatic data remains active status in CEIC and is reported by General Administration of Customs. The data is categorized under China Premium Database’s International Trade – Table CN.JKF: RMB: HS90: Optical, Photographic, Cinematographic, Measuring, Checking, Precision, Medical or Surgical Instruments and Apparatus; Parts and Accessories Thereof.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Macau Gaming: Number of Gaming Table data was reported at 6,598.000 Unit in Sep 2018. This records an increase from the previous number of 6,588.000 Unit for Jun 2018. Macau Gaming: Number of Gaming Table data is updated quarterly, averaging 5,302.000 Unit from Mar 2005 (Median) to Sep 2018, with 55 observations. The data reached an all-time high of 6,598.000 Unit in Sep 2018 and a record low of 1,226.000 Unit in Mar 2005. Macau Gaming: Number of Gaming Table data remains active status in CEIC and is reported by Gaming Inspection and Coordination Bureau. The data is categorized under Global Database’s Macau SAR – Table MO.Q019: Number of Casinos and Gaming Tables.
https://data.gov.tw/licensehttps://data.gov.tw/license
The information provided includes: file name, link, update date, and other field data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Indonesia Export: Value: Plotters (Drafting Tables and Machines), Whether or Not Automatic data was reported at 0.000 USD mn in May 2024. This records an increase from the previous number of 0.000 USD mn for Feb 2022. Indonesia Export: Value: Plotters (Drafting Tables and Machines), Whether or Not Automatic data is updated monthly, averaging 0.000 USD mn from Feb 2022 (Median) to May 2024, with 2 observations. The data reached an all-time high of 0.000 USD mn in May 2024 and a record low of 0.000 USD mn in Feb 2022. Indonesia Export: Value: Plotters (Drafting Tables and Machines), Whether or Not Automatic data remains active status in CEIC and is reported by Statistics Indonesia. The data is categorized under Indonesia Premium Database’s Foreign Trade – Table ID.JAH089: Foreign Trade: by HS 8 Digits: Export: HS90: Optical, Photographic, Cinematographic, Measuring, Checking, Medical or Surgical Instruments and Apparatus, Parts, and Accessories.
**Please Note: the data provided in this table is updated weekly.This is designed to provide the public with information regarding inspections of all geographically fixed personal services premises in Waterloo Region. Please be advised that the results of all inspections posted here describe what the Public Health Inspector (PHI) observed on the date of inspection. This data is not intended to guarantee the conditions of a personal services premise at all times and should not be relied upon for that purpose. No endorsement of any personal services premise, or the products or services offered by a personal service premise, is expressed or implied by any information, material or content included in this data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Semantic Table Search Dataset
Resource: A Large Scale Test Corpus for Semantic Table Search
Check out the README for more information.
This statistic shows the results of a survey conducted in the United States in 2018 on online shopping. Some 36 percent of the respondents stated that they are checking the return policies of an online shop when they have found a product the probably want to buy.The Survey Data Table for the Statista survey Online-Shopping in the U.S. 2018 contains the complete tables for the survey including various column headings.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Pairwise comparisons of branch lengths between UCSC and study tree models.
https://data.gov.tw/licensehttps://data.gov.tw/license
Taichung City 105 1-12 months male conscription examination statistics table data
**Please Note: the data provided in this table is updated weekly.This is designed to provide the public with information regarding inspections of all geographically fixed personal services premises in Waterloo Region. Please be advised that the results of all inspections posted here describe what the Public Health Inspector (PHI) observed on the date of inspection. This data is not intended to guarantee the conditions of a personal services premise at all times and should not be relied upon for that purpose. No endorsement of any personal services premise, or the products or services offered by a personal service premise, is expressed or implied by any information, material or content included in this data.
This report details the numbers, sources and types of allegations of maladministration reported to STA’s maladministration team in the academic year 2023 to 2024, relating to the:
It also presents the numbers of amendments and annulments to results made.
This Statistical First Release (SFR) provides provisional 2012/2013 information on the achievements of both eligible pupils in the phonics screening check and those pupils at the end of key stage 1 (KS1) in their national curriculum teacher assessments by level, gender, ethnicity, English as a first language, free school meal eligibility, special educational need and the income deprivation affecting children index (IDACI). Breakdowns of achievement for disadvantaged pupils were added to both the phonics and key stage 1 tables on 12th December 2013.
The phonics screening check introduced in 2012 is a statutory assessment for all children in year 1 (typically aged 6). All state-funded schools with a year 1 cohort must administer the checks. Those pupils who did not meet the standard in year 1 or who were not tested are re-checked at the end of year 2 (typically aged 7).
The KS1 teacher assessments measure pupils’ attainment against the levels set by the national curriculum. They measure the extent to which pupils have the specific knowledge, skills and understanding which the national curriculum expects pupils to have mastered by the end of KS1. The national curriculum standards have been designed so that by the end of KS1, pupils are expected to reach Level 2.
The figures contained within this publication combine the information gathered through the school census in January 2013 and the 2013 phonics and key stage 1 achievement data. This release provides information at national and local authority (LA) level and includes attainment by pupil characteristics. Tables showing a breakdown of KS1 attainment by area of pupil residence are included in this release.
The key points from this release are:
In the 2013 phonics screening check 69% of year 1 pupils met the expected standard of phonic decoding, an increase of 11 percentage points since 2012. As in 2012, girls outperformed boys with 73% achieving the expected standard compared to 65% of boys. All characteristic groupings have seen proportions achieving the expected standard increase in the last year.
In 2013 85% of pupils at the end of year 2 met the expected standard of phonic decoding. This includes the proportion reaching the expected standard of phonic decoding in year 1, 2012 and those re-checked or taking for the first time in 2013.
The 2013 key stage 1 (KS1) teacher assessments show that the percentage of pupils achieving the expected level has continued to increase in all subjects. The largest increases, also seen in 2012, are in reading and writing where the percentage of pupils achieving the expected level has increased by a further 2 percentage points. The percentages of pupils achieving the expected level in speaking and listening, science and mathematics have improved by 1 percentage point.
Girls continue to outperform boys in terms of the percentage of pupils reaching the expected level at KS1. The biggest difference is in writing with a gap of 9 percentage points, 1 percentage point lower than in 2012.
Sally Marshall
National Pupil Database and Small Area Statistics team
01142 742 317
https://assets.publishing.service.gov.uk/media/66437c544f29e1d07fadc717/vehicles-and-drivers-tables-index.ods">Tables index (ODS, 15 KB)
These statistics from inspections of independent schools in England are made up of:
Official statistics are produced impartially and free from political influence.
These inspection of further education and skills in England statistics are made up of:
Official statistics are produced impartially and free from political influence.
https://github.com/MIT-LCP/license-and-dua/tree/master/draftshttps://github.com/MIT-LCP/license-and-dua/tree/master/drafts
Electronic Health Records (EHRs) are integral for storing comprehensive patient medical records, combining structured data (e.g., medications) with detailed clinical notes (e.g., physician notes). These elements are essential for straightforward data retrieval and provide deep, contextual insights into patient care. However, they often suffer from discrepancies due to unintuitive EHR system designs and human errors, posing serious risks to patient safety. To address this, we developed EHRCon, a new dataset and task specifically designed to ensure data consistency between structured tables and unstructured notes in EHRs. EHRCon was crafted in collaboration with healthcare professionals using the MIMIC-III EHR dataset, and includes manual annotations of 4,101 entities across 105 clinical notes checked against database entries for consistency. EHRCon has two versions, one using the original MIMIC-III schema, and another using the OMOP CDM schema, in order to increase its applicability and generalizability.