MétaCan
Menu
Back to cohort
Record W2776836056 · doi:10.4088/jcp.16cr10967

Cognitive Planning Neural Correlates in a Pediatric Monozygotic Twin Pair Discordant for Obsessive-Compulsive Disorder

2017· letter· en· W2776836056 on OpenAlexafffund
Fern Jaspers‐Fayer, Juliana Negreiros, Sarah Lin, Laura Belschner, S. Evelyn Stewart

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2017
Typeletter
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsProvincial Health Services AuthorityBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsPsychologyAnterior cingulate cortexPrefrontal cortexCognitionDorsolateral prefrontal cortexFunctional magnetic resonance imagingNeuroscienceNeuroimagingSuperior temporal gyrusNeural correlates of consciousnessPosterior cingulateAudiologyMedicine

Abstract

fetched live from OpenAlex

Article AbstractBecause this piece does not have an abstract, we have provided for your benefit the first 3 sentences of the full text.To the Editor: Pediatric obsessive-compulsive disorder (OCD) is a debilitating illness characterized by intrusive thoughts and repetitive behaviors. Patients may exhibit poorer executive function, such as cognitive planning. Substantial overlap exists between brain areas implicated in OCD pathology and those involved in planning (eg, dorsolateral prefrontal cortex, posterior parietal cortex, extrastriate visual cortex, anterior cingulate cortex, inferior frontal gyrus), and functional magnetic resonance imaging (MRI) demonstrates that participants with OCD perform poorly and show less regional brain responsivity as task load increases in comparison to healthy controls. This robust finding could be useful in the domain of precision medicine, as it normalizes after cognitive-behavioral therapy and may be useful in individual activation profiles that could predict treatment response.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.011
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 head0.057
GPT teacher head0.408
Teacher spread0.351 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Clinical PsychiatrySame topicObsessive-Compulsive Spectrum DisordersFrench-language works237,207