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Record W4221008442 · doi:10.1038/s41398-022-01845-w

Correction: Methodology for clinical genotyping of CYP2D6 and CYP2C19

2022· erratum· en· W4221008442 on OpenAlexaff
Beatriz Carvalho Henriques, Amanda Buchner, Xiuying Hu, Yabing Wang, Vasyl Yavorskyy, Keanna Wallace, Rachael Dong, Kristina Martens, Michael S. Carr, Bahareh Behroozi Asl, Joshua Hague, Sudhakar Sivapalan, Wolfgang Maier, Mojca Zvezdana Dernovšek, Neven Henigsberg, Joanna Hauser, Daniel Souery, Annamaria Cattaneo, Ole Mors, Marcella Rietschel, Gerald Pfeffer, Stacey Hume, Katherine J. Aitchison

Bibliographic record

VenueTranslational Psychiatry · 2022
Typeerratum
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsAlberta Hospital EdmontonUniversity of CalgaryWomen and Children’s Health Research InstituteUniversity of Alberta
Fundersnot available
KeywordsGenotypingCYP2C19CYP2D6MedicineMEDLINEPsychologyInformation retrievalComputer scienceInternal medicineGenotypeGeneticsPolitical scienceBiology

Abstract

fetched live from OpenAlex

The original version of this article unfortunately contained an error in the affiliations and in Table 1. The original article has been corrected.

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)0.010
metaresearch head score (Gemma)0.134
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.134
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0030.003
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0670.047

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 head0.370
GPT teacher head0.551
Teacher spread0.181 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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