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Record W3099515847 · doi:10.1002/jaba.797

Replicating stimulus‐presentation orders in discrimination training

2020· article· en· W3099515847 on OpenAlexaff
Samantha Bergmann, Maria Turner, Tiffany Kodak, Laura L. Grow, Courtney Meyerhofer, Haven Niland, Kaitlyn Edmonds

Bibliographic record

VenueJournal of Applied Behavior Analysis · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyStimulus (psychology)Autism spectrum disorderAudiologyAutismStimulus controlCognitive psychologyDevelopmental psychologyClinical psychologyNeuroscience

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.285
GPT teacher head0.401
Teacher spread0.116 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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