Bibliographic record
Abstract
The American Academy of Neurology (AAN) has been a leader in developing clinical practice guidelines. Both the Quality Standards Subcommittee (QSS) and the Therapeutics and Technology Assessment Subcommittee (TTA) produce guidelines: “systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances.”1 These guidelines aim to improve the quality of patient care and possibly the efficiency in use of health care resources.2 Clinical practice guidelines are typically based on 1) the best available peer-reviewed scientific evidence, 2) a consensus of expert opinion, or 3) a combination of these two sources.3 The AAN’s guideline development process aims at the evidence-based category, with little use for expert opinion. Recently, methodologic standards for assessing the quality of guidelines have been suggested.2 Three dimensions of guideline characteristics are considered: 1) development and format, 2) evidence identification and summary, and 3) formulation of recommendations. Using these criteria, only 43% of the standards were met across a broad swathe of published guidelines.2 Of concern, only 15% of guidelines explicitly graded the scientific evidence and only 13% graded recommendations according to the strength of the evidence. These two critical standards are strengths of the AAN guideline development …
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 | 0.014 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.038 | 0.047 |
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".