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Record W50275616 · doi:10.1007/bf03016668

Consent in the crossfire

2008· editorial· fr· W50275616 on OpenAlexaff
Joan C. Bevan

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2008
Typeeditorial
Languagefr
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsObservational studyInformed consentAuditMedicineQuality assuranceEthics committeeClinical trialFamily medicineAlternative medicinePolitical scienceInternal medicineAccountingBusinessPathology

Abstract

fetched live from OpenAlex

formed, written consent for inclusion in randomized controlled clinical trials, the use of their medical re cords in case reports/series, or for quality assurance and medical audit studies. In 2001, a review of 1,189 publications in six lead ing anesthesia journals found documented ethics com mittee approval in 71%, and individual written consent in 66% of the articles. rates varied among the journals with the highest rates (94% and 87%) for prospective clinical trials, and the lowest (2% and 3%) for case reports/series. Observational studies, prospective and retrospective, ranked in between. 1 Shortly after these results were published, most countries introduced leg islation to protect the privacy of individuals and pre

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)0.063
metaresearch head score (Gemma)0.207
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.063
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.207
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0030.011
Scholarly communication0.0090.013
Open science0.0030.005
Research integrity0.0330.037
Insufficient payload (model declined to judge)0.0120.007

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 head0.048
GPT teacher head0.357
Teacher spread0.309 · 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
GenreEditorial

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

Citations1
Published2008
Admission routes1
Has abstractyes

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