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Record W2074899501 · doi:10.1016/j.apmr.2013.12.010

Elevating the Quality of Disability and Rehabilitation Research: Mandatory Use of the Reporting Guidelines

2014· editorial· en· W2074899501 on OpenAlexaboutno aff
Leighton Chan, Allen W. Heinemann, Jason A. Roberts

Bibliographic record

VenueArchives of Physical Medicine and Rehabilitation · 2014
Typeeditorial
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
FundersU.S. National Library of Medicine
KeywordsRehabilitationQuality (philosophy)Mandatory reportingMedicinePhysical medicine and rehabilitationPhysical therapyMedical emergencyInjury preventionPoison control

Abstract

fetched live from OpenAlex

With the remarkable growth of disability- and rehabilitation-related research in the last decade, it is imperative that we support the highest quality research possible. With cuts in research funding, rehabilitation research is now under a microscope like never before, and it is critical that we put our best foot forward.

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)0.819
metaresearch head score (Gemma)0.927
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.181
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8190.927
Meta-epidemiology (narrow)0.0040.008
Meta-epidemiology (broad)0.0120.009
Bibliometrics0.0210.021
Science and technology studies0.0090.019
Scholarly communication0.0310.031
Open science0.0130.016
Research integrity0.0310.032
Insufficient payload (model declined to judge)0.0070.010

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 head0.730
GPT teacher head0.613
Teacher spread0.116 · 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
DomainReporting
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

Citations60
Published2014
Admission routes1
Has abstractyes

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