In response: Lateral Knee Pain Requires a Thorough Assessment and Adequate, Best-Practice Intervention
Bibliographic record
Abstract
In response: Lateral Knee Pain Requires a Thorough Assessment and Adequate, Best-Practice InterventionThe article referred to in Mr. van de Water's letter is a prospective case series bringing attention to soft-tissue restriction as a potential source of knee dysfunction.The article describes treatment of chronic pain conditions seven months or more after injury, diagnosis (which included ITBS), and on-going care.Editors agree that description of and any reevaluation of those diagnoses, as well as some outcomes, could have been addressed more clearly.The manuscript author agrees regarding best practice, and describes that in both the introduction and discussion.The best practice scenario applies at the time of injury; the treatment provided addresses a seven-month post-injury chronic pain condition.The IJTMB believes the case series effectively highlights the importance of considering soft-tissue restriction in cases of lateral knee pain when more common diagnoses have been ruled out or treatment otherwise remains ineffective.
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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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.022 | 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; 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".