Alcohol Effects on Central Nervous System Gene Expression in Genetic Animal Models
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".