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Record W3193234131 · doi:10.51731/cjht.2021.98

Initiation of Biologic Disease-Modifying Antirheumatic Drugs for Rheumatoid Arthritis: A Budget Impact Analysis

2021· article· en· W3193234131 on OpenAlexaboutno aff
Jesse Elliot, Tessa Cornelissen, Bernice Tsoi, Karen Lee

Bibliographic record

VenueCanadian Journal of Health Technologies · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsAntirheumatic drugsRheumatoid arthritisBiosimilarMedicineJurisdictionAntirheumatic AgentsDrugPhysical therapyPharmacologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

There is variation across Canadian jurisdictions in time to the initiation of biologic disease-modifying antirheumatic drug (bDMARD) therapy among adults with rheumatoid arthritis. From a pan-Canadian perspective, harmonizing time to bDMARD initiation across jurisdictions may result in savings to publicly funded drug plans in some jurisdictions but increased drug expenditures in others. The extent of savings or increased costs is dependent on jurisdiction, the number of new bDMARD users, and whether patients receive a biosimilar or originator bDMARD.

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)0.006
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.584

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0060.015
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.031
GPT teacher head0.329
Teacher spread0.298 · 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
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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