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Record W2595948025 · doi:10.3389/fncel.2017.00046

Six Years of Research on the National Institute of Mental Health’s Research Domain Criteria (RDoC) Initiative: A Systematic Review

2017· review· en· W2595948025 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2017
Typereview
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsResearch Domain CriteriaMental healthPsychologyCognitionMental illnessCognitive sciencePsychiatry

Abstract

fetched live from OpenAlex

Six years have passed since the National Institute of Mental Health (NIMH) in the United States launched the Research Domain Criteria (RDoC) initiative. The RDoC introduces a framework for research on the biology of mental illness that integrates research findings across multiple levels of information. The framework outlines constructs that represent specific quantifiable dimensions of behavior (e.g., responses to acute threat, cognitive control) and corresponding units of analysis that can be used to study the constructs, beginning at the levels of genes, molecules, cells, circuits and physiology, and moving up to behaviors and self-reports. In this systematic review, a literature search was conducted to synthesize empirical research published since the proposal of the framework that incorporated the RDoC. Forty-eight peer-reviewed scholarly articles met eligibility criteria for the review. Studies differed according to whether they analyzed RDoC constructs and units of analysis within vs. between clinically-diagnosed and non-psychiatric samples. The most commonly studied constructs were subsumed within the domains of Negative Valence Systems, Positive Valence Systems and Cognitive Systems, providing initial results which primarily connected genetics, brain circuits and physiology research findings with behavior and self-reports. Prospects for future research adopting the RDoC matrix and utilizing a dimensional approach to studying the biology of mental illness are discussed.

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)0.040
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.537
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.002
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 head0.672
GPT teacher head0.621
Teacher spread0.051 · 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