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Record W1991835965 · doi:10.1037/0097-7403.33.2.79

Rats take correct novel routes and shortcuts in an enclosed maze.

2007· article· en· W1991835965 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Experimental Psychology Animal Behavior Processes · 2007
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyWater mazePath (computing)Elevated plus mazeAdult maleNeuroscienceArtificial intelligenceComputer scienceMedicine

Abstract

fetched live from OpenAlex

In 3 experiments, rats were allowed to travel selected routes along the internal alleys of a cross-maze that led from one distinctive end box to another. The maze and procedures used were designed to control the rats' ability to use intrinsic and extrinsic cues to their location in the maze; thus, only the internal geometry of the maze could be learned and used to travel between one end box and another. After an initial exploration phase, rats were given novel routes and shortcut tests that involved peripheral alleys not before traveled. Rats chose the correct novel path or shortcut significantly above chance on some tests in Experiments 1 and 2 and significantly better than a control group in Experiment 3. The findings suggest that rats were able to compute novel routes and shortcuts within the maze on the basis of limited experience with the internal geometry of the maze.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.029
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

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

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 head0.164
GPT teacher head0.439
Teacher spread0.276 · 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