Bibliographic record
Abstract
This text offers the reader a good overview of a relatively rare group of disorders -the idiopathic inflammatory myopathies (IIM).Although concise, the chapters are sufficiently detailed to provide readers with an opportunity to expand their knowledge and whet their appetite to read further.This book has internationally acclaimed myositis experts contributing chapters.The contents are divided into 5 major sections: Overview, Differential Diagnosis, Important Disease Subtypes, Investigations, Treatment and Outcome.The chapters are succinct, generally well written, and recently referenced, although references in some chapters should be expanded and updated.Cross-referencing from chapter to chapter could be improved to make the text feel more cohesive.Key point summaries at the beginning of each chapter are useful to the reader and reflect and summarize the chapter's contents.Figures and tables are used very effectively throughout the text and provide relevant details as well as clinical approaches to many topics including classification criteria, toxic myopathies, genetic myopathies, myositis-specific antibodies, and core set measures of activity.The photographs, however, are very small, generally of poor quality, and mostly black and white, obscuring important histological and clinical features.This severely limits their usefulness to the reader.I would have liked a chapter devoted to a clinical-histological-serological approach to diagnosis, treatment, and prognosis of IIM, briefly alluded to in several chapters but not clearly articulated.The chapter on Aetiology and Pathogenesis was particularly well done.This text is very readable and has valuable information about a relatively rare group of muscle disorders.I would recommend it to students of rheumatology, including residents and fellows, as well as practicing rheumatologists.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.102 | 0.070 |
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".