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Record W1989939332 · doi:10.1016/j.ajhg.2014.12.013

CLPB Mutations Cause 3-Methylglutaconic Aciduria, Progressive Brain Atrophy, Intellectual Disability, Congenital Neutropenia, Cataracts, Movement Disorder

2015· article· en· W1989939332 on OpenAlexafffund
Saskia B. Wortmann, Szymon Ziętkiewicz, Maria Kousi, Radek Szklarczyk, Tobias B. Haack, Søren W. Gersting, Ania C. Muntau, Aleksandar Raković, G. Herma Renkema, Richard J. Rodenburg, Tim M. Strom, Thomas Meitinger, M. Estela Rubio‐Gozalbo, Elżbieta Chruściel, Felix Distelmaier, Christelle Golzio, Joop H. Jansen, Clara D.M. van Karnebeek, Yolanda Lillquist, Thomas Lücke, Katrin Õunap, Riina Žordania, Joy Yaplito‐Lee, Hans van Bokhoven, Johannes N. Spelbrink, Frédéric M. Vaz, Mia L. Pras‐Raves, Rafał Płoski, Ewa Pronicka, Christine Klein, Michèl A.A.P. Willemsen, Arjan P.M. de Brouwer, Holger Prokisch, Nicholas Katsanis, Ron A. Wevers

Bibliographic record

VenueThe American Journal of Human Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsChild and Family Research InstituteBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of PittsburghKoninklijke Nederlandse Akademie van WetenschappenNational Alliance for Research on Schizophrenia and DepressionBrain and Behavior Research Foundation
KeywordsMedicineAtrophyIntellectual disabilityNeutropeniaPediatricsCataractsPathologyInternal medicineOphthalmologyPsychiatryChemotherapy

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.299
Teacher spread0.282 · 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 designCase report
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

Citations135
Published2015
Admission routes2
Has abstractno

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