Bibliographic record
Abstract
in the article that is a subject of Samuelson and Perone’s commentary, we reported the results of a study in which 15-month-olds were presented with novel target objects that possessed a non-obvious property—a novel sound. We found that infants attempted to elicit the novel sound on test objects that matched the target object in shape, more so than on test objects that matched the target in color or texture. Critically, this pattern of behavior emerged only in a condition in which none of the test objects could actually produce a sound. We concluded that this selective generalization to shape-matched objects reflects infants’ expectation that objects similar in shape share non-obvious properties. In their commentary, Samuelson and Perone (S&P) challenged our interpretation on both empirical and theoretical grounds. In what follows, we respond to these challenges by first addressing incorrect representations of our findings and then discussing the theoretical challenges presented in their commentary.
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 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.059 | 0.071 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".