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Record W4408245738 · doi:10.1002/jeab.70002

Separate and combined effects of operant <scp>ABA</scp> renewal mitigation strategies

2025· article· en· W4408245738 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Experimental Analysis of Behavior · 2025
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsBrock University
Fundersnot available
KeywordsContext (archaeology)Extinction (optical mineralogy)FadingPsychologyDiscriminative modelReinforcementContext effectComputer scienceSocial psychologyArtificial intelligenceTelecommunicationsChannel (broadcasting)BiologyMathematics

Abstract

fetched live from OpenAlex

Due to the undesirable effects of operant renewal for behavioral interventions, recent research has advocated for the advancement of renewal mitigation strategies. One strategy includes the use of extinction cues, which are stimuli used to establish discriminative control over responding in the second context that are subsequently transferred to the initial context. A second strategy involves context fading, which refers to progressively increasing the similarity between the second context and the initial context. The current study evaluated the separate and combined effects of these techniques using a preclinical human laboratory arrangement. Participants were exposed to the extinction cue strategy, the context fading strategy, both strategies, or neither strategy during a three-phase ABA renewal procedure using differential reinforcement of an alternative response combined with extinction. The results indicated that context fading or combining context fading with an extinction cue was effective at mitigating renewal. The use of an extinction cue alone reduced renewal relative to the control group, but this difference was not statistically significant. The results are discussed in terms of methodological and theoretical differences across strategies as well as implications for future research on renewal mitigation strategies.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.353
Teacher spread0.317 · 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