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Record W3047820483 · doi:10.1192/bjo.2020.71

Refractoriness of aggressive behaviour to pharmacological treatment: cortical thickness analysis in autism spectrum disorder

2020· article· en· W3047820483 on OpenAlexaff
Flavia Venetucci Gouveia, Jürgen Germann, Gabriel A. Devenyi, Rosa M. C. B. Morais, Ana Paula Milla dos Santos, Erich Talamoni Fonoff, Clement Hamani, Helena Brentani, M. Mallar Chakravarty, Raquel Chacon Ruiz Martinez

Bibliographic record

VenueBJPsych Open · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSunnybrook Health Science CentreMcGill University Health CentreMcGill UniversityDouglas Mental Health University InstituteUniversity of TorontoUniversity Health NetworkHealth Sciences CentreSunnybrook Hospital
Fundersnot available
KeywordsAutism spectrum disorderRefractory (planetary science)Refractory periodNeurosciencePsychologyAutismMedicinePsychiatryInternal medicineBiology

Abstract

fetched live from OpenAlex

Aggressive behaviour is a highly prevalent and devastating condition in autism spectrum disorder resulting in impoverished quality of life. Gold-standard therapies are ineffective in about 30% of patients leading to greater suffering. We investigated cortical thickness in individuals with autism spectrum disorder with pharmacological-treatment-refractory aggressive behaviour compared with those with non-refractory aggressive behaviour and observed a brain-wide pattern of local increased thickness in key areas related to emotional control and overall decreased cortical thickness in those with refractory aggressive behaviour, suggesting refractoriness could be related to specific morphological patterns. Elucidating the neurobiology of refractory aggressive behaviour is crucial to provide insights and potential avenues for new interventions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.090
GPT teacher head0.375
Teacher spread0.285 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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