MétaCan
Menu
Back to cohort
Record W4394332015 · doi:10.6084/m9.figshare.20416476

Additional file 1 of Association between dual sensory impairment and risk of mortality: a cohort study from the UK Biobank

2022· dataset· en· W4394332015 on OpenAlexaff
Xinyu Zhang, Yueye Wang, Wei Wang, Wenyi Hu, Xianwen Shang, Huan Liao, Yifan Chen, Katerina Kiburg, Yu Huang, Xueli Zhang, Shulin Tang, Honghua Yu, Xiaohong Yang, Mingguang He, Zhuoting Zhu

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsBiobankCohortAssociation (psychology)Dual (grammatical number)Cohort studyMedicineDemographyGerontologyPsychologyInternal medicineBioinformaticsBiologySociologyArt

Abstract

fetched live from OpenAlex

Additional file 1: Supplemental Table 1.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.457
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.4570.060

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.307
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicInfrared Thermography in MedicineFrench-language works237,207