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Record W4404287372 · doi:10.1177/20451253241286319

Plain Language Summary of Publication: A comparison of once-monthly and once-every-2-months injectable formulations of aripiprazole in people with schizophrenia

2024· review· en· W4404287372 on OpenAlexfundno aff
Leslie Citrome, Pedro Such, Murat Yıldırım, Jessica Madera‐McDonough, Clodagh Beckham, Na Jin, Suzanne Watkin, Zhen Zhang, Frank Larsen, Matthew Harlin

Bibliographic record

VenueTherapeutic Advances in Psychopharmacology · 2024
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersNational Eye InstituteIdorsia PharmaceuticalsH. Lundbeck A/SOtsuka PharmaceuticalEisaiSunovionAllerganHLS TherapeuticsPfizerTeva Pharmaceutical IndustriesEli Lilly and CompanyBristol-Myers Squibb
KeywordsAripiprazoleSchizophrenia (object-oriented programming)Section (typography)PsychiatryPsychologyMedicineClinical psychologyComputer science

Abstract

fetched live from OpenAlex

The purpose of this summary is to explain key findings from a study that included people with schizophrenia, as described in two separate articles (see the 'Further Information' section for more details). The study compared a new formulation of aripiprazole, given as an injection once every 2 months, with a once‑monthly injection of aripiprazole.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.042
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0420.007

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 head0.033
GPT teacher head0.427
Teacher spread0.394 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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