Bibliographic record
Abstract
To the Editor: Thank you very much to Dr Öhman for taking the time to read and comment1 on our recent article, “Adapting to Higher Demands: Using Innovative Methods to Treat Infants Presenting With Torticollis and Plagiocephaly.”2 We appreciate the work that her group has done on identifying/setting reference values of neck range of motion (ROM) in infants under 1 year old who are healthy.3 The clinical findings that we observed in our group, which suggest that 110° to 120° of rotation and 65° to 75° of lateral flexion are mean values in this age group are supportive of her research. Although in our abovementioned article we suggested that there were no reference values for ROM and no standardized way to measure infants’ neck ROM, we concur that it would have been more accurate to state that there is no consensus in the literature on these 2 points. As noted in Ohman's research report3 mean values have differed by study,4,5 and even within her research the values differed by age and also when measured at multiple time points in infants that are healthy. Taking into consideration that our population was infants presenting with torticollis and therefore had an unaffected side that could be used for comparison, we maintain that using “full” and “not full,” “1/2,” and “3/4” was the most appropriate measurement technique in our context. Thank you for the opportunity to clarify our position and strengthen the research and literature on torticollis and plagiocephaly. Dominique Suprenant, BScPt Ottowa, Ontario, Canada
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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 | 0.003 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.021 | 0.019 |
| Insufficient payload (model declined to judge) | 0.032 | 0.020 |
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".