Bibliographic record
Abstract
PURPOSE OF REVIEW: The past 18 months have seen multireader validation exercises assessing the reliability and discriminatory properties of MRI, longitudinal data evaluating the prognostic significance of lesions observed on MRI, and data from clinical trials assessing the predictive capacity of MRI for major clinical response. Studies using new MRI-based technologies in ankylosing spondylitis have also been described. RECENT FINDINGS: The reliability and discrimination of scoring systems for both sacroiliac joint and spinal inflammation using MRI are now sufficiently well validated to be used in the short-term clinical trial assessment of the anti-inflammatory efficacy of novel therapeutic agents. The finding of inflammatory lesions on MRI is also of prognostic significance for structural damage. MRI examination contributes to clinical and laboratory evaluation in the selection of patients likely to respond to antitumor necrosis factor agents. Newer MRI-based techniques such as whole-body MRI permit a broader scope of diagnostic ascertainment. SUMMARY: MRI continues to assume an increasingly important role in the diagnostic, prognostic, and therapeutic assessment of patients with ankylosing spondylitis.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".