Additional file 1 of Efficacy and safety of biosimilar CT-P17 versus reference adalimumab in subjects with rheumatoid arthritis: 24-week results from a randomized study
Bibliographic record
Abstract
Additional file 1: Supplementary methods, including Table S1 Study centers and IRB/IEC information, Full inclusion and exclusion criteria, Table S2 Schedule of assessments (screening and treatment period 1), and Analysis populations. Table S3 ACR50 and ACR70 response rates and hybrid ACR scores up to week 24 (ITT population). Table S4 Mean (SD) Ctrough overall and by ADA status (PK population). Figure S1 Mean (±SD) Ctrough by ADA status (PK population). Table S5 Mean (SD) scores by domain for PRE-SIAQ and POST-SIAQ (usability population). Table S6 Study drug–related TESAEs (safety population). Table S7 TEAEs by System Organ Class reported by ≥2% of subjects in either treatment group (safety population). Table S8 Summary of immunogenicity results (safety population). Table S9 ACR20 response rate at week 24 by ADA status (ITT population). Table S10 Treatment-emergent adverse events by ADA status (safety population). Figure S2 Historical data for ACR20 response rate at week 24 for reference or biosimilar adalimumab (50 mg/ml), compared with CT-P17 or reference adalimumab (100 mg/ml) treatment in the current study (ITT population).
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.866 | 0.079 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".