Social attribution skills of children born preterm at very low birth weight
Bibliographic record
Abstract
Children born prematurely at very low birth weight (<1500 g) are at increased risk for impairments affecting social functioning, including autism spectrum disorders (e.g., Johnson et al., 2010). In the current study, we used the Happé-Frith animated triangles task (Abell, Happé, & Frith, 2000) to study social attribution skills in this population. In this task, typical viewers attribute intentionality and mental states to shapes, based on characteristics of their movements. Participants included 34 preterm children and 36 full-term controls, aged 8-11 years. Groups were comparable in terms of age at test, gender, handedness, and socioeconomic status; they also performed similarly on tests of selective attention/processing speed and verbal intelligence. Relative to full-term peers, preterm children's descriptions of the animations were less appropriate overall; they also overattributed intentionality/mental states to randomly moving shapes and underattributed intentionality/mental states to shapes that seemed to be interacting socially. Impairments in the ability to infer the putative mental states of triangles from movement cues alone were most evident in children displaying more "autistic-like" traits, and this may reflect atypical development of and/or functioning in, or atypical connections between, parts of the social brain.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".