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Are Brain Responses to Emotion a Reliable Endophenotype of Schizophrenia? An Image-Based Functional Magnetic Resonance Imaging Meta-analysis

2022· review· en· W4283322746 on OpenAlexaff
Anna M. Fiorito, André Alemán, Giuseppe Blasi, Josiane Bourque, Hengyi Cao, Raymond C. K. Chan, Asadur Chowdury, Patricia Conrod, Vaibhav A. Diwadkar, Vina M. Goghari, Salvador M. Guinjoan, R.E. Gur, Ruben C. Gur, Jun Soo Kwon, Johannes Lieslehto, Paulina B. Lukow, Andreas Meyer‐Lindenberg, Gemma Modinos, Tiziana Quarto, Michael J. Spilka, Venkataram Shivakumar, Ganesan Venkatasubramanian, Mirta F. Villarreal, Yi Wang, Daniel H. Wolf, Je‐Yeon Yun, É. Fakra, Guillaume Sescousse

Bibliographic record

VenueBiological Psychiatry · 2022
Typereview
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of TorontoUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCilagH. Lundbeck A/SFondation Pierre Deniker pour la Recherche et la Prévention en Santé MentaleOtsuka PharmaceuticalFondation de FranceBundesministerium für Bildung und ForschungAgence Nationale de la RechercheUniversity of AlabamaInstitut de FranceSeventh Framework ProgrammeAbbVieMeso Scale DiagnosticsSanofiOtsuka AmericaBristol-Myers SquibbAstraZenecaDeutsche Forschungsgemeinschaft
KeywordsEndophenotypeFunctional magnetic resonance imagingPsychologySchizophrenia (object-oriented programming)Meta-analysisNeuroimagingAmygdalaBrain activity and meditationNeuroscienceMagnetic resonance imagingAudiologyMedicinePsychiatryCognitionElectroencephalographyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.218
GPT teacher head0.353
Teacher spread0.135 · 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.

Study designMeta-analysis
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

Citations13
Published2022
Admission routes1
Has abstractno

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