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Record W4417211800 · doi:10.21203/rs.3.rs-8286229/v1

Multicenter retrospective study on effectiveness, reported side effects, and cognitive outcomes of SSRIs in 22q11.2 deletion syndrome

2025· preprint· en· W4417211800 on OpenAlexaff
Caren Latrèche, Valentina Mancini, Marija Dvojakovska, Leila Kushan, Fatouma Mchangama, Tal Cohen, J. Spapens, Lieke Reijn, Covadonga M. Díaz‐Caneja, Hayford Acheampong, Lotte Troch, Elfi Vergaelen, Annick Vogels, Ann Swillen, Claudia Vingerhoets, Erik Boot, Celso Arango, Fleur P. Velders, Ania Fiksinski, Thérèse van Amelsvoort, Doron Gothelf, Carrie E. Bearden, Boris Chaumette, Maude Schneider, Stéphan Eliez

Bibliographic record

VenueResearch Square · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsSte. Anne's Hospital
FundersCilagNational Institute of Mental HealthInstituto de Salud Carlos IIIHorizon 2020 Framework ProgrammeAssociation Nationale de la Recherche et de la TechnologieMinisterio de Ciencia e InnovaciónStanford Maternal and Child Health Research InstituteCentro de Investigación Biomédica en Red de Salud MentalEisaiEuropean Regional Development FundEuropean CommissionH. Lundbeck A/SFundación Alicia KoplowitzNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungHORIZON EUROPE Framework ProgrammeAgence Nationale de la RechercheNational Science Foundation
KeywordsCognitionMoodAnxietyObservational studyLongitudinal studyMood disordersAffect (linguistics)Intelligence quotientCognitive decline

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.031
GPT teacher head0.410
Teacher spread0.379 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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