Where am I? Distal cues use requires sensitivity to start location change in the rat.
Bibliographic record
Abstract
Place learning is impaired when a single plus maze is moved between adjacent locations 33-120 cm apart. This maze translation creates distinct start locations but maintains a single goal location with respect to distal cues. Hippocampal cell recording data suggest the majority of place fields are tied to apparatus boundaries, not to distal cues, when an apparatus is moved these distances to the left or right. Thus, rats may fail to appreciate the existence of multiple start locations with respect to distal cues when the maze is moved in this way and their start location on the surface is constant. Performance on the single plus maze problem was improved when texture cues were correlated with different start locations. Place learning was supported when multiple start locations were provided on a single large surface (double plus maze), even though rats did not explore the entire surface. Place learning was also supported when random extensions were added to a double plus maze such that start locations, relative to surface boundaries, were not informative as to goal location. This outcome suggests sensitivity to multiple start locations is required for distal cue use in translational place problems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".