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The Spectrum of MORC2-Related Disorders: A Potential Link to Cockayne Syndrome

2023· article· en· W4319993262 on OpenAlexafffund
Seth A. Stafki, Johnnie Turner, Hannah R. Littel, Christine C. Bruels, Don Truong, Ursula Knirsch, Georg M. Stettner, U. U. Graf, Wolfgang Berger, Maria Kinali, Heinz Jungbluth, Christina A. Pacak, Jayne Hughes, Amytice Mirchi, Alexa Derksen, Catherine Vincent‐Delorme, Arjan F. Theil, Geneviève Bernard, D. Ellis, Hiva Fassihi, Alan R. Lehmann, Vincent Laugel, Shehla Mohammed, Peter B. Kang

Bibliographic record

VenuePediatric Neurology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéU.S. Food and Drug AdministrationCanadian Institutes of Health ResearchKWF KankerbestrijdingCompute CanadaOncode InstituteMcGill UniversityTakeda Pharmaceuticals U.S.A.
KeywordsCockayne syndromeOMIM : Online Mendelian Inheritance in ManPhenotypeGeneticsBiologyMicrocephalyDNA repairAutism spectrum disorderNucleotide excision repairBioinformaticsAutismMedicineGenePsychiatry

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.012
GPT teacher head0.235
Teacher spread0.224 · 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 teacher head, not a consensus.

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

Citations17
Published2023
Admission routes2
Has abstractno

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