Problem Variables that Promote Incubation Effects
Bibliographic record
Abstract
Abstract Three studies sought to determine whether incubation effects could be reliably generated in a problem‐solving task. Experimental variables manipulated were the duration of the interval between two problem‐solving opportunities and the activity performed by the problem solvers during the interval. A multi‐solution anagram task was used which required problem solvers to generate five‐letter words from the letters in a ten‐letter “starter” word until they could produce no more words. After a break (the incubation period) the problem solvers returned to the anagram task anew. Some participants also engaged in an activity related to the anagram task during the break which was expected to prime potential solutions that would emerge during the second problem‐solving attempt. In all conditions problem solvers were able to generate new responses after the break, thus demonstrating a reliable incubation effect. The optimal incubation period was between 15 and 30 min long. The priming task increased the number of solutions to the anagram task on the second attempt, suggesting that exposure to solution ideas during the incubation period may facilitate an incubation effect during problem solving.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".