OrthoEvidenceTM: a clinical resource for evidence-based orthopedics
Bibliographic record
Abstract
The prevalence of musculoskeletal issues in clinical practice, and the limited focus placed upon musculoskeletal conditions by current electronic summary resources, highlights the need for a resource that provides access to simple and concise summaries of top-quality orthopedic literature for orthopedic surgeons and allied healthcare professionals. OrthoEvidence™ is an online clinical resource that addresses the paucity of adequate evidence-based summary tools in the field of orthopedic surgery. OrthoEvidence™ uses a rigorous, transparent, and unique process to review, evaluate, and summarize high quality research studies and their implications for orthopedic clinical practice. Randomized controlled trials and meta-analyses are identified and reviewed by an expert medical writing team, who prepare Advanced Clinical Evidence (ACETM) reports: one or two detailed pages including critical appraisals and synopses of key research. These timely and targeted reports provide a clear understanding about the quality of evidence associated with each summarized study, and can be organized by users to identify trending information. OrthoEvidence™ allows members to use their time efficiently and to stay current by having access to a breadth of timely, high-quality research output. OrthoEvidence™ is easily accessible through the internet and is available at the point-of-care, which allows treating orthopedic surgeons and allied health professionals to easily practice the principles of evidence-based medicine within their clinical practices..
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".