PHYSICAL ASSESSMENT IN SURFERS: GUIDELINES FOR HEALTH PROFESSIONALS - PART 1 UPPER QUARTER
Bibliographic record
Abstract
In Brazil, surfing has gained popularity in recent decades, driven by beautiful beaches, good wave conditions and the spirit of adventure that permeates Brazilian culture, but also increasing the risk of injuries. During surfing, the surfer spends most of the time lying prone on the board while paddling, placing heavy demands on the musculoskeletal system in the cervical and lumbar spine, as well as in the shoulder region, which are important points for complaints of chronic injuries among surfers. The objective of the present study was to update musculoskeletal assessment of the upper quarter, related to physical examination and functional tests that can be applied to surfers. This is an update study based on an integrative review through a bibliographical survey in which national and international journals indexed in the scientific databases Scielo and PubMed were evaluated, developed and analyzed by a group of experts in the area of surf medicine and health composed of physical educator, physiotherapists and sports doctors. This guideline study compiled important information regarding the prevalence of upper quarter musculoskeletal injuries in surfers, guiding the surfer's outpatient assessment, considering the specificity of the sport and biomechanical gesture involved.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".