Decoding The Diagnostic Triad: A 2018-2020 Study on the Clinical, MRI and Arthroscopic Correlation in Meniscal And ACL Injuries at BSMMU
Bibliographic record
Abstract
This prospective study aimed to evaluate the correlation between clinical and arthroscopic findings in knee injuries and compare them with MRI-based diagnoses. The research was conducted at BSMMU, Dhaka, between 2018 and 2020. The study population consisted of patients with knee injuries, specifically those with cruciate ligament and/or meniscal injuries that led to persistent knee instability for at least 1.5 months, remained unresponsive to conservative treatment, and did not have osteoarthritis or intra-articular fractures. Patients with a history of knee surgery, osteoarthritis, or ligament and meniscal injuries associated with intra-articular fractures were excluded. A total of 30 eligible cases were consecutively included in the study
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".