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Record W4396993518 · doi:10.1016/j.neuchi.2024.101567

The use and abuse of survival analysis and Kaplan-Meier curves in surgical trials

2024· review· en· W4396993518 on OpenAlexaff
Tim E. Darsaut, Alan R. Rheaume, Miguel Chagnon, Jean Raymond

Bibliographic record

VenueNeurochirurgie · 2024
Typereview
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversité de MontréalUniversity of Alberta HospitalCentre Hospitalier de l’Université de MontréalHealth Sciences Centre
Fundersnot available
KeywordsSurvival analysisMedicineDemographyPsychologyInternal medicineSociology

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)0.079
metaresearch head score (Gemma)0.199
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.199
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.008
Bibliometrics0.0070.010
Science and technology studies0.0000.002
Scholarly communication0.0050.006
Open science0.0040.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.136
GPT teacher head0.387
Teacher spread0.251 · 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
DomainMethods
GenreReview

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

Citations5
Published2024
Admission routes1
Has abstractno

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