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Record W4200304533 · doi:10.1093/bib/bbab522

An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer’s disease

2021· article· en· W4200304533 on OpenAlexaff
Cuixiang Lin, Hong‐Dong Li, Chao Deng, Weisheng Liu, Shannon Erhardt, Fang‐Xiang Wu, Xing‐Ming Zhao, Yuanfang Guan, Jun Wang, Daifeng Wang, Bin Hu, Jianxin Wang

Bibliographic record

VenueBriefings in Bioinformatics · 2021
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of Neurological Disorders and StrokeNational Institute on AgingArizona Biomedical Research CommissionHigher Education Discipline Innovation ProjectNational Natural Science Foundation of ChinaArizona Department of Health Services
KeywordsGeneDiseaseDementiaAlzheimer's diseaseTranscriptomeGenome-wide association studyClinical Dementia RatingBiologyPhenotypeGenetic associationNeuroscienceBioinformaticsComputational biologyGeneticsMedicineGene expressionSingle-nucleotide polymorphismGenotypePathology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

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

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 head0.051
GPT teacher head0.329
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2021
Admission routes1
Has abstractyes

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