Bibliographic record
Abstract
The current dataset incorporates multimodal brain imaging and creativity test data from a sample of 66 healthy young adults, all of whom were healthy right-handed English speakers, aged 22 to 35, with normal or corrected-to-normal hearing and vision. The participants completed measures of divergent thinking (Abbreviated Torrance Test for Adults; ATTA), everyday creativity (Creative Behaviour Inventory; CBI), and creative achievement (Creative Achievement Questionnaire; CAQ), consistent with the known multidimensional nature of creativity. They also completed high-resolution anatomical scans (T1-weighted and T2-weighted), diffusion tensor imaging scans, and resting state fMRI scans. The data were originally used in the article Neuroimaging predictors of creativity in healthy adults by Sunavsky and Poppenk [1] to test a set of confirmatory predictions regarding the volumetric, structural connectivity, and functional connectivity correlates of creativity. The data are uniquely high-dimensional in measuring both multiple dimensions of creativity as well as multimodal brain data, and may be valuable to researchers for testing models of individual differences in creativity, or who are seeking to integrate multiple datasets for large-scale, multi-site analysis of creativity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".