Bibliographic record
Abstract
This paper reviews the current work on mouse genetics, brain, and behaviour in my laboratory. It starts with an historical account of our research and shows how certain research themes, such as olfaction, learning, social behaviour, and environmental effects in rodents have led to our current research on behavioural phenotyping of inbred, mutant, knockout, and transgenic mice. We are concerned with finding neural and behavioural sequelae to genetic manipulations in mice and use a battery of tests to detect behaviours that are altered in genetically modified mice. In this way we are working to dissociate neural and behavioural effects of different gene manipulations in mouse models of neurodegenerative diseases. Sensory, motor, cognitive, affective, and social behaviours may all be affected by gene manipulation, thus careful behavioural techniques, with attention to the mice themselves, the apparatus, and procedure, experimenter variables, and environmental effects are necessary in order to determine a reliable and valid mouse behavioural phenotype. As both the genome and the environment have significant effects on the behavioural phenotype, our future research will utilize an epigenetic approach to examine how environmental cues modulate gene expression in the behavioural phenotyping of transgenic mice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".