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Record W3002052870 · doi:10.1503/cmaj.74072

Patient-oriented research can be meaningful for clinicians and trialists as well as patients

2020· letter· en· W3002052870 on OpenAlexaffvenue
Thalia S. Field, Vanessa Dizonno, Sarah Park, Michael D. Hill

Bibliographic record

VenueCanadian Medical Association Journal · 2020
Typeletter
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsRivaroxabanVenous thrombosisStroke (engine)MedicineThrombosisIntensive care medicineSurgeryInternal medicineEngineering

Abstract

fetched live from OpenAlex

We read with interest the CMAJ Analysis by Aubin and colleagues,[1][1] which identified issues in developing and measuring the impact of patient-oriented research. We are studying cerebral venous thrombosis (CVT), an uncommon cause of stroke, in a national trial (Study of rivaroxaban in CeREbral

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)0.358
metaresearch head score (Gemma)0.619
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.642
Threshold uncertainty score0.791

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3580.619
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0040.004
Science and technology studies0.0060.025
Scholarly communication0.0240.037
Open science0.0070.011
Research integrity0.0730.085
Insufficient payload (model declined to judge)0.0080.009

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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
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

Citations1
Published2020
Admission routes2
Has abstractyes

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