Additional file 1 of 2025 position statement on active outdoor play: process and methodology
Bibliographic record
Abstract
Supplementary Material 1: Supplemental file 1: Title: AOP10 Leadership Team and Steering Committee Members. Description: Full list of AOP10 leadership team and steering committee member names, affiliated countries and organizations. Supplemental file 2: Environmental Scan to Inform the AOP10 Project Scope. Description: Summary of environmental scan results and table describing the scan results based on item type (e.g., an outdoor play movement, organization, conference, event, project or document). Supplemental file 3: Summary Statements Developed by ChatGPT to Inform the AOP10 Conceptual Framework. Description: Table outlining the common/main themes of identified position statement and expressions of interest, summarized by ChatGPT. Supplemental file 4: Text Mining Search Strategy. Description: Table outlining the search strategy used for the text mining analysis identifying common themes related to active outdoor play. Supplemental file 5: Systematic Review Contributions Strategy. Description: Table outlining the strategy to ensure equitable contributions to systematic reviews among large author groups as part of the AOP10 project.
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 | 0.011 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.913 | 0.235 |
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".