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Record W2508908821 · doi:10.1038/ejhg.2016.111

Who should have access to genomic data and how should they be held accountable? Perspectives of Data Access Committee members and experts

2016· article· en· W2508908821 on OpenAlexaff
Mahsa Shabani, Adrian Thorogood, Pascal Borry

Bibliographic record

VenueEuropean Journal of Human Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMcGill UniversityMcGill Genome Centre
FundersVlaamse regering
KeywordsSanctionsData sharingEnforcementBusinessInternet privacyPublic relationsData accessCompliance (psychology)Downstream (manufacturing)TrustworthinessComputer sciencePolitical sciencePsychologyMedicineMarketingLawAlternative medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.356
metaresearch head score (Gemma)0.491
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3560.491
Meta-epidemiology (narrow)0.0010.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.003
Science and technology studies0.0270.043
Scholarly communication0.0480.030
Open science0.0120.027
Research integrity0.0710.096
Insufficient payload (model declined to judge)0.0080.002

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 head0.677
GPT teacher head0.561
Teacher spread0.116 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractno

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