The author responds
Bibliographic record
Abstract
Thank you Ms Scolnik for your insightful comments. However, we respectfully disagree that your suggestions would have led to a “deeper understanding” of the issues at hand. First, there is no evidence that Canadian parents are more likely to seek emergency medical care for female children than male children. Second, when examining the sports-injury literature, there is good evidence that males represent the overwhelming majority of children presenting to emergency departments with injuries (1). Third, since the implementation of the Hockey Canada National Safety Program in 1994, there have been major efforts to educate trainers and have them be present at all games involving both sexes and across all age groups (2). As emergency physicians and clinical investigators, our intent was to describe the injury patterns observed in female and male players and explore whether we could identify patterns that could lead to targeted injury prevention strategies. While it is important to elucidate factors that affect the decision to seek medical attention, the reasons highlighted do not reflect the societal shift in attitudes toward female sports over the past decade.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.091 | 0.052 |
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".