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Record W7019838673

An investigation into the effect of OCD tendencies in reveral learning

2021· dissertation· en· W7019838673 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2021
Typedissertation
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsObsessive compulsiveCognitionFlexibility (engineering)Cognitive flexibilityStimulus (psychology)Scale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

Individuals diagnosed with Obsessive-Compulsive Disorder (OCD) appear to have reduced cognitive flexibility and slower reaction times when adjusting associations that they have attached to previous behaviours and creating new ones. In addition, research has found deficits in reversal learning related to patients of OCD. The current study therefore investigated the relationship between OCD and reversal learning. In contrast to previous studies, the findings displayed no significance between the Obsessive-Compulsive Inventory – Revised (OCI-R) scores and reversal learning variables such as adjusting stimuli or selecting the same stimulus depending on the positive/negative response received and correct number of responses. As hypothesised, lower scores on the Vancouver Obsessional Compulsive Inventory – Mental Contamination Scale (VOCI-MC) were found to predict higher number of correct responses. Future research could focus on such variables on a larger scales as well as incorporating clinically diagnosed patients in addition to sub-clinical. Results of the current study add to the growing literature related to OCD. Such literature being crucial in gaining a greater understanding of the disorder and are especially relevant to the current global pandemic.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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