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Record W2058933839 · doi:10.1136/bmj.g4966

Data to support assisted dying

2014· letter· en· W2058933839 on OpenAlexaffabout
Jonathan Downar, Marguerite A. Boisvert, David Roy Smith

Bibliographic record

VenueBMJ · 2014
Typeletter
Languageen
FieldSocial Sciences
TopicLegal and cultural studies analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsData scienceComputer scienceWorld Wide WebMedicineInformation retrieval

Abstract

fetched live from OpenAlex

The editors of The BMJ have taken an important stand in the assisted death debate in the UK.1 In Canada, we are also coming to terms with this issue. Quebec province has legalised it, and our supreme court is set to hear a case that could strike down the federal laws that prohibit it.2 In Canada, about 80% of the public supports the legalisation of assisted …

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)0.068
metaresearch head score (Gemma)0.437
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.068
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.437
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0060.007
Scholarly communication0.0080.013
Open science0.0040.009
Research integrity0.0300.034
Insufficient payload (model declined to judge)0.0420.010

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 head0.190
GPT teacher head0.394
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2014
Admission routes2
Has abstractyes

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Same venueBMJSame topicLegal and cultural studies analysisFrench-language works237,207