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Strain differences in three measures of ethanol intoxication in mice: the screen, dowel and grip strength tests

2003· article· en· W1996337656 on OpenAlexafffund
John C. Crabbe, C. J. Cotnam, Andy J. Cameron, Jason P. Schlumbohm, Justin S. Rhodes, Pamela Metten, Douglas Wahłsten

Bibliographic record

VenueGenes Brain & Behavior · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of Alberta
FundersNational Institute on Alcohol Abuse and AlcoholismNatural Sciences and Engineering Research Council of CanadaU.S. Public Health Service
KeywordsDowelGrip strengthStrain (injury)EthanolMedicineBiologyPhysiologyInternal medicineMaterials scienceComposite materialBiochemistry

Abstract

fetched live from OpenAlex

Mice from 8 to 21 inbred strains were tested for sensitivity to ethanol intoxication using a range of doses and three different measures: the screen test, the dowel test and a test of grip strength. Strains differed under nearly all conditions. For the dowel test, two dowel widths were employed, and mice were tested immediately or 30 min after ethanol. For the dowel and screen tests, low doses failed to affect some strains, and the highest doses failed to discriminate among mice, maximally affecting nearly all. For grip strength, a single ethanol dose was used, and mice of all strains were affected. Pharmacokinetic differences among strains were significant, but these could not account for strain differences in intoxication. For doses and test conditions in the middle range, there were only modest correlations among strain means within a test. In addition, genotypic correlations across tests were modest to quite low. These results suggest that different specific versions of a test reflect the influence of different genes, and that genetic influences on different tests were also distinct.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.080
GPT teacher head0.306
Teacher spread0.226 · 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 designBench or experimental
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

Citations74
Published2003
Admission routes2
Has abstractyes

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