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Record W2584009011 · doi:10.3899/jrheum.161558

Back to the Future of Rheumatology

2017· editorial· en· W2584009011 on OpenAlexvenueno aff
YVONNE PIGOTT, CARLYLE M. RODRIGO, Earl D. Silverman

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typeeditorial
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsVettingMedicineThe InternetReprintLibrary scienceAssociate editorMedical educationWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

The medical cycle of discovery from researcher to editor to reviewer to publisher to researcher and back again — often re-engaging the same players in different roles — is a model for vetting and sharing medical information that inspired longtime Journal Editor Duncan Gordon1 (Figure 1). Figure 1. The medical discovery cycle; adapted with permission1. Little did anyone know at that time — not Duncan Gordon, the associate editors, reviewers, and authors — to what extent the discovery process would speed up and multiply itself, in particular with the emergence of electronic resource networks on the Internet. Today, electronic resources are apparent … Address reprint requests to Dr. E.D. Silverman; e-mail: jrheum{at}jrheum.com

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.415
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.286
Teacher spread0.279 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

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