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Record W2899599177 · doi:10.1503/cmaj.180447

Patient engagement in research related to accelerated surgical care and treatment for hip fracture

2018· article· en· W2899599177 on OpenAlexafffundvenue
Michael McGillion, Lee Lin-Rogano, Flávia K. Borges

Bibliographic record

VenueCanadian Medical Association Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersMcMaster University
KeywordsHip fractureMedicineComputer scienceSurgeryOsteoporosisPathology

Abstract

fetched live from OpenAlex

KEY POINTS Each year, millions of adults worldwide experience a hip fracture with devastating consequences.[1][1]–[3][2] Following hip fracture, the 30-day mortality rate is 9.3% (95% confidence interval [CI] 8.8%–9.9%) for men and 5.2% (95% CI 4.9%–5.4%) for women.[4][3] Those who survive to

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)0.033
metaresearch head score (Gemma)0.171
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.171
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0270.003

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 head0.054
GPT teacher head0.376
Teacher spread0.321 · 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 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

Citations4
Published2018
Admission routes3
Has abstractyes

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