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Record W4292543993 · doi:10.1002/cjp2.293

<scp>PRAME</scp> protein expression in <scp>DICER1</scp>‐related tumours

2022· erratum· en· W4292543993 on OpenAlexaff
Paul S. Thorner, Anne‐Sophie Chong, Javad Nadaf, Naciba Benlimame, Paula Marrano, Rose Chami, Lili Fu, William D. Foulkes

Bibliographic record

VenueThe Journal of Pathology Clinical Research · 2022
Typeerratum
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsHospital for Sick ChildrenMcGill UniversityMcGill Genome CentreMcGill University Health CentreJewish General HospitalUniversity of Toronto
Fundersnot available
KeywordsMinor (academic)Protein expressionExpression (computer science)Molecular biologyChemistryComputer scienceCombinatoricsBiologyMathematicsBiochemistryProgramming languagePhilosophyGeneHumanities

Abstract

fetched live from OpenAlex

The authors have identified some minor errors in the published version of the supplementary tables for this paper. Corrected tables are provided here and supersede the previously published versions. The authors apologise for any inconvenience caused. c.3080_3081insCT, p.Gln1028CysfsTer39 c.5487_5490delAGTC, p.Val1830GlyfsTer7

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)0.001
metaresearch head score (Gemma)0.007
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 score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0410.016

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 head0.125
GPT teacher head0.456
Teacher spread0.331 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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