Suboptimal choice and initial‐link requirement
Bibliographic record
Abstract
Pigeons (n = 14) were trained in a concurrent-chains suboptimal choice procedure that tested the effect of an increased ratio requirement in the initial links. Fixed-ratio 1 and 25 conditions were manipulated within subjects in a counterbalanced order. In all conditions, distinct terminal-link stimuli on a suboptimal alternative signaled either primary reinforcement (20% of the time) or extinction (80% of the time). On an optimal alternative, two distinct terminal-link stimuli each signaled a 50% chance of primary reinforcement. Preference for the suboptimal alternative was significantly attenuated, and in some birds completely reversed, by the larger response requirement irrespective of condition order. This larger response requirement also generated a notable increase in between-subject variability. A measure of cumulative choice responding is introduced to mitigate the problems associated with traditional session averages. Ordinal predictions of some current theories of suboptimal choice are also considered in light of the results.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".