Pain in Child Health from 2002 to 2015: The early years of an international research training initiative
Bibliographic record
Abstract
Background The 2018 Global Year for Excellence in Pain Education, an initiative of the International Association for the Study of Pain, brought worldwide attention to the need for education that crosses narrow disciplinary boundaries, addresses up-to-date research methods and findings, and encourages teamwork among trainees and mentors at different levels of training and with different perspectives.Aims This commentary describes the development of Pain in Child Health (PICH), an interdisciplinary training program for researchers in pediatric pain at the undergraduate, graduate, and postdoctoral levels of training.Methods Based on documentation of the structure, training processes, leadership, and membership of PICH, we outline its organization and its challenges and accomplishments over the first 12 years of its growth into a well-known international program.Results and Conclusions Pain in Child Health began as a Strategic Training Initiative of the Canadian Institutes of Health Research in 2002 and developed into an international research training consortium featuring cross-site and cross-discipline mentorship and collaboration. PICH trainees and alumni have contributed extensively to the current scientific literature on children’s pain. PICH could serve as a possible model for training and mentorship in other specialized health research domains within and outside thestudy of pain.
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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 | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".