Bibliographic record
Abstract
Recent decades have seen the introduction of many new therapeutics into pediatric rheumatology practice, particularly biologic disease-modifying antirheumatic drugs (bDMARD). These advances are a result of the biotechnological revolution in the pharmaceutical industry, specific legislation for the development of pediatric medicines, and large international collaborative networks. The bDMARD have increased the probability of achieving challenging therapeutic goals such as remission in juvenile idiopathic arthritis (JIA). According to data from recent inception cohort studies in Canada and Germany, 75–81% of newly diagnosed JIA patients reached inactive disease during the first year of treatment, with 21–35% of cases receiving bDMARD1,2. There is growing evidence that rapid and aggressive disease control through early effective treatment is crucial for the further course and outcome of JIA3,4,5. For this reason, an international task force of 30 pediatric rheumatologists has recommended that a clinically inactive disease should be reached within the first 6 months of treatment by means of a treat-to-target approach6. If this therapeutic target, or at least minimal (or low) disease activity, has not been achieved, escalation of therapy (e.g., the use of one bDMARD or switching to another bDMARD) is recommended. However, we are currently not in a position to predict drug outcomes, either at the start of treatment or at a time when treatment needs to be modified or escalated to maximize therapeutic outcomes. Despite the advances in treatment, managing JIA still often follows a trial-and-error principle. Patients with JIA may have to spend a lifetime testing medications that may not be effective in treating their condition7. With the ever-increasing number of medications, family and provider decision making is becoming increasingly complex, including the choice of … Address correspondence to Dr. K. Minden, Charité – Universitätsmedizin Berlin, Department of Rheumatology and Clinical Immunology, German Rheumatism Research Center, Epidemiology Unit, Chariteplatz 1, 10117 Berlin, Germany. Email: minden{at}drfz.de.
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 | 0.023 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.016 | 0.035 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.017 | 0.033 |
| Insufficient payload (model declined to judge) | 0.040 | 0.012 |
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".