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Record W2991103112 · doi:10.1093/cvr/cvz294

Cardiovascular research highlights from the UK Biobank: opportunities and challenges

2019· article· en· W2991103112 on OpenAlexfundno aff
Zahra Raisi‐Estabragh, Steffen E. Petersen

Bibliographic record

VenueCardiovascular Research · 2019
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
FundersCircle Cardiovascular ImagingEuropean CommissionNational Institute for Health and Care ResearchBritish Heart FoundationNational Institute on Handicapped Research
KeywordsBiobankMedicineBioinformaticsBiology

Abstract

fetched live from OpenAlex

This is a pre-copyedited, author-produced version of an article accepted for publication in Cardiovascular Research following peer review. The version of record Zahra Raisi-Estabragh, Steffen E Petersen, Cardiovascular research highlights from the UK Biobank: opportunities and challenges, Cardiovascular Research, Volume 116, Issue 1, 1 January 2020, Pages e12–e15, https://doi.org/10.1093/cvr/cvz294 is available online at: https://doi.org/10.1093/cvr/cvz294 .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.267
GPT teacher head0.360
Teacher spread0.093 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations25
Published2019
Admission routes1
Has abstractyes

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