Experienced crawlers avoid real and water drop‐offs, even when they are walking
Bibliographic record
Abstract
Abstract Crawling experience was recently linked to crawling and walking infants’ avoidance of falling on real and water cliffs, whereas walking experience had no effect on walkers’ avoidance behavior (Burnay et al., 2021). In the current study, the behavior of 25 infants was analyzed on the Real Cliff/Water Cliff apparatus using a longitudinal study design. Infants were tested as experienced crawlers (Mcrawling = 2.93 months, SD = 1.07), novice walkers (Mwalking = 0.68 months, SD = 0.29), and experienced walkers (Mwalking = 4.90 months, SD = 0.92). Infants avoided falling on both cliffs when tested as experienced crawlers and their behavior was not different when tested as novice or experienced walkers. These findings confirmed the effect of crawling experience on crawling and walking infants’ avoidance of falls from heights and into water and the transfer of perceptual learning from crawling to walking postures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".