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Record W2103681272 · doi:10.1002/bin.308

Immediate and subsequent effects of differential reinforcement of other behavior and noncontingent matched stimulation on stereotypy

2010· article· en· W2103681272 on OpenAlexaff
Marc J. Lanovaz, Malena Argumedes

Bibliographic record

VenueBehavioral Interventions · 2010
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsQuebec Rehabilitation Research NetworkUniversité de MontréalCentre de réadaptation Lethbridge-Layton-Mackay
Fundersnot available
KeywordsDifferential reinforcementPsychologyReinforcementStereotypyDevelopmental psychologyStimulationAutismAudiologyNeuroscienceMedicineSocial psychologyAmphetamine

Abstract

fetched live from OpenAlex

Abstract A three‐component multiple‐schedule and brief reversals were used to examine the effects of differential reinforcement of other behavior (DRO) and noncontingent matched stimulation (NMS) on the automatically reinforced mouthing of a child with autism. Both DRO and NMS decreased immediate engagement in mouthing, but NMS produced larger reductions in the behavior. Furthermore, NMS produced subsequent effects (i.e., when the treatment was withdrawn) similar to those of prior access, whereas DRO marginally increased subsequent engagement in mouthing. The results suggest that NMS was a functionally matched intervention for mouthing. Implications for the assessment and treatment of stereotypy and applications for future research are discussed. Copyright © 2010 John Wiley & Sons, Ltd.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.377
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), 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

Citations19
Published2010
Admission routes1
Has abstractyes

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