Bibliographic record
Abstract
Objective Pre–post-randomized design evaluated The Blue Dog, a dog safety software program. Methods 76 children aged 3.5–6 years completed 3 tasks to evaluate dog safety pre- and postintervention: (a) pictures (recognition of safe/risky behavior), (b) dollhouse (recall of safe behavior via simulated dollhouse scenarios), and (c) live dog (actual behavior with unfamiliar live dog). Following preintervention evaluation, children were randomly assigned to dog or fire safety conditions, each involving 3 weeks of home computer software use. Results Children using Blue Dog had greater change in recognition of risky dog situations than children learning fire safety. No between-group differences emerged in recall (dollhouse) or engagement (live-dog) in risky behavior. Families enjoyed using the software. Conclusions Blue Dog taught children knowledge about safe engagement with dogs, but did not influence recall or implementation of safe behaviors. Dog bites represent a significant pediatric injury concern and continued development of effective interventions is needed. Key words computer software; dog bites; injury; intervention; prevention; safety.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.241 | 0.034 |
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".