Levels of Evidence Are Not the Whole Story
Bibliographic record
Abstract
Levels of evidence (LOE) are classification systems that use a hierarchal structure to indicate where the research in question may fall in regard to the strength of the recommendations. They have been used in some form in medical literature since the 1970s and have continued to be refined for ease of use by the practicing physician. The purpose of this article is to define LOE as commonly used in the orthopaedic literature and to highlight that LOE alone is not always sufficient for assessing the quality of the evidence presented. Examples of research at different LOE are presented and discussed, highlighting the importance of critical appraisal when using these guidelines.
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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 | 0.224 | 0.673 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.033 | 0.037 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.023 | 0.053 |
| Insufficient payload (model declined to judge) | 0.014 | 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; the direct Gemma label and the distilled Codex classifier 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".