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Record W2199027905 · doi:10.1097/nmd.0000000000000435

The National Institute of Mental Health Research Domain Criteria

2015· review· en· W2199027905 on OpenAlexaff
Joel Paris, Laurence J. Kirmayer

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2015
Typereview
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill University
Fundersnot available
KeywordsResearch Domain CriteriaPsychopathologyPsychosocialMental healthPsychologyPremisePhenomenology (philosophy)Classification of mental disordersCognitionPerspective (graphical)Domain (mathematical analysis)PsychiatryNosologyClinical psychologyPsychotherapistCognitive psychologyEpistemologyPrevalence of mental disordersComputer science

Abstract

fetched live from OpenAlex

The National Institute of Mental Health is actively promoting Research Domain Criteria as a new model for the research on mental disorders. Research Domain Criteria approaches disorders through a matrix, linking units of analysis with domains, based on the assumption that psychopathology reflects abnormal connectivity in the brain. This review suggests that the Research Domain Criteria perspective is likely to fail to provide an adequate basis for clinical psychiatric theory and practice. First, it uses models from neuroscience that are insufficiently developed. Second, it is based on the premise that mental phenomena and mental disorders can be reduced to neural activity, without consideration of cognition, experience, and social interaction. Third, it downplays psychosocial factors in psychopathology and treatment. Research Domain Criteria may therefore prove inadequate for providing a neuroscientific basis for psychiatric nosology and treatment and needs to be supplemented with a broader view that incorporates insights from social sciences, psychology, and phenomenology.

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)0.024
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0110.010
Science and technology studies0.0020.005
Scholarly communication0.0050.004
Open science0.0050.006
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0100.008

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 head0.432
GPT teacher head0.602
Teacher spread0.170 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations43
Published2015
Admission routes1
Has abstractyes

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