Teamwork in hip preservation: the ISHA 2019 Annual Scientific Meeting
Bibliographic record
Abstract
Hip preservation surgery is now an established part of orthopedic surgery and sports medicine. This report describes the key findings of the 11th Annual Scientific Meeting of International Society for Hip Arthroscopy-the International Hip Preservation Society-in Madrid, Spain from 16 to 19 October 2019. Lectures, seminars and debates explored the most up-to-date and expert views on a wide variety of subjects, including: diagnostic problems in groin pain, buttock pain and low back pain; surgical techniques in acetabular dysplasia, hip instability, femoroacetabular impingement syndrome, labral repair and reconstruction, cartilage defects, adolescent hips and gluteus medius and hamstring tears; and new ideas about femoral torsion, hip-spine syndrome, hip capsule surgery, impact of particular sports on hip injuries, registries, robotics and training for hip preservation specialists. Surgeons, sports physicians, radiologists and physiotherapists looking after young people with hip problems have an increasingly sophisticated armoury of ideas and techniques with which to help their patients. The concept of hip preservation has developed incredibly fast over the last decade; now it is clear that the best results can only be achieved by a multidisciplinary team working together. The 2020s will be the decade of 'Teamwork in Hip Preservation'.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".