Audiovisual integration in infant language acquisition: Different patterns in typically developing infants and those at elevated risk for autism spectrum disorder
Bibliographic record
Abstract
摘要： 多模态感知机制对婴儿期语言习得至关重要, 其中视听整合在典型发育婴儿的语言能力发展中起着关键作用。相比之下, 高风险自闭症谱系障碍(ASD)婴儿在此整合过程中常面临挑战。典型的言语感知发展轨迹强调面部特征加工的重要性——对眼部与嘴部区域的注意能促进语言学习。实证研究表明, 4.5月龄的婴儿已具备视听整合能力, 这种能力可有效预测后期语言发展水平。而高风险ASD婴儿则表现出社会性注意减少和视听整合功能受损, 此类缺陷可能破坏常规语言习得路径。因此, 早期干预策略应优先采用基于生物学的感觉引导方法, 重点增强多感官整合能力, 而非仅针对注意行为进行训练。理解这些机制不仅能深化对典型语言发展的认知, 更能为制定早期干预方案提供实证基础, 从而支持高风险ASD群体的语言习得。
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".