A Simple and Reliable Test of Olfactory Learning and Memory in Mice
Bibliographic record
Abstract
The present paper describes a quick and efficient method for assessing olfactory discrimination learning in mice. In training mice received trials in which one odor (CS+) was paired with sugar and another odor (CS-) was paired with no sugar. When the mice were subsequently placed in a chamber with CS+ odor at one end and CS- odor at the other, they spent more time digging in CS+ than in CS- odor. In Experiment 2 mice trained with this procedure and tested after 60 days also spent more time digging in CS+ than CS- in the test phase, indicating that this olfactory discrimination task is effective for assessing long-term memory. In addition to the outbred strain of CD1 mice used in Experiments 1 and 2, C57Bl/6NCr/BR and DBA/2NCr/BR mice used in Experiment 3 also acquired this learned odor discrimination. Moreover, Experiment 4 showed that DBA animals were capable of acquiring this odor discrimination after receiving only two training trials (one exposure each to CS+ and CS-) per day for 4 days.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".