Replicating stimulus‐presentation orders in discrimination training
Bibliographic record
Abstract
Children with autism spectrum disorder (ASD) are taught conditional discriminations often during early intervention. Auditory-visual conditional discrimination (AVCD) training requires the presentation of multiple antecedent stimuli, and the order of stimulus presentation varies in the literature. This series of studies replicated previous literature on stimulus-presentation order in AVCD training. In Experiment 1, we compared sample-first and comparisons-first arrangements in 8 comparisons with 4 participants with ASD. For 3 participants, both presentations were efficacious. For 1 participant, the sample-first order was more likely to be efficacious. In Experiment 2, we added a sample-first-with-repetition arrangement and conducted 6 comparisons with 5 participants with ASD. Across comparisons, all 3 presentations were efficacious. Considerations for teaching AVCD to children with ASD and suggestions for further evaluation and examination of efficacy and efficiency are discussed.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".