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Record W4389966161 · doi:10.1016/j.autrev.2023.103504

Implementation of regulatory guidance for JAK inhibitors use in patients with immune-mediated inflammatory diseases: An international appropriateness study

2023· review· en· W4389966161 on OpenAlexaff
Virginia Solitano, Paola Facheris, Magnus Petersen, Ferdinando D’Amico, Michela Ortoncelli, Daniel Aletaha, Pablo A. Olivera, Thomas Bieber, Sofía Ramiro, Subrata Ghosh, Maria Antonietta D’Agostino, Britta Siegmund, Isabelle Chary‐Valckenaere, Ailsa Hart, Lorenzo Dagna, Fernando Magro, Renaud Felten, Paulo Gustavo Kotze, Vipul Jairath, Antonio Costanzo, Lars Erik Kristensen, Laurent Peyrin‐Biroulet, Silvio Danese

Bibliographic record

VenueAutoimmunity Reviews · 2023
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsWestern UniversitySinai Health SystemMcGill University Health CentreLunenfeld-Tanenbaum Research Institute
FundersGalápagosPfizer
KeywordsMedicineRisk assessmentFamily medicinePharmacovigilanceLikert scaleInternal medicineAdverse effectPsychology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.209
GPT teacher head0.497
Teacher spread0.288 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2023
Admission routes1
Has abstractno

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