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Record W4306292574 · doi:10.3899/jrheum.220909

Drs. Bessette and Kinch reply

2022· letter· en· W4306292574 on OpenAlexaffvenue
Louis Bessette, C. Kinch

Bibliographic record

VenueThe Journal of Rheumatology · 2022
Typeletter
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsEli Lilly (Canada)Université LavalNovartis (Canada)Pfizer (Canada)
Fundersnot available
KeywordsMedicinePeripheral blood mononuclear cellRheumatoid arthritisTofacitinibPeripheral bloodImmunologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

We thank Dr. Tchetina for their interest in our article,1 and we appreciate the opportunity to respond to their Letter to the Editor.2 In the letter and their recent publication, Tchetina et al describe the utility of gene expression analyses using peripheral blood mononuclear cells (PBMCs) from patients with rheumatoid arthritis (RA) to predict clinical response to tofacitinib (TOF).2,3

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)0.004
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.025
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0250.029
Insufficient payload (model declined to judge)0.0090.009

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 head0.015
GPT teacher head0.267
Teacher spread0.253 · 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 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
Published2022
Admission routes2
Has abstractyes

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