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Alcohol Effects on Central Nervous System Gene Expression in Genetic Animal Models

2005· article· en· W2025563084 on OpenAlexaboutno aff
William J. McBride, Robnet T. Kerns, Zachary A. Rodd, Wendy N. Strother, Howard J. Edenberg, Joel G. Hashimoto, Kristine M. Wiren, Michael F. Miles

Bibliographic record

VenueAlcoholism Clinical and Experimental Research · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsnot available
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsVentral tegmental areaGeneMicroarrayGene expressionCandidate geneMicroarray analysis techniquesNeuroscienceBasal gangliaEthanolCentral nervous systemGeneticsBasal (medicine)BiologyEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

This article summarizes the proceedings of a symposium presented at the 2004 annual meeting of the Research Society on Alcoholism in Vancouver, British Columbia, Canada. The organizers and chairs were William J. McBride and Michael F. Miles. The presentations were (1) Molecular Triangulation on Gene Expression Patterns in Behavioral Responses to Acute Ethanol, by Robnet T. Kerns; (2) Gene Expression in Limbic Regions After Ethanol Self-Infusion Into the Posterior Ventral Tegmental Area, by Zachary A. Rodd; (3) Microarray Analysis of CNS Limbic Regions of Inbred Alcohol-Preferring and -Nonpreferring rats and Effects of Alcohol Drinking, by Wendy N. Strother and Howard J. Edenberg; and (4) Microarray Analysis of Mouse Lines Selected for Chronic Ethanol Withdrawal Severity: The Convergence of Basal, Ethanol Regulated, and Proximity to Ethanol Quantitative Trait Loci to Identify Candidate Genes, by Joel G. Hashimoto and Kristine M. Wiren.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.074
GPT teacher head0.406
Teacher spread0.332 · 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 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

Citations16
Published2005
Admission routes1
Has abstractyes

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