An Exploratory Study on DRD2 and Creative Potential
Bibliographic record
Abstract
One critical step toward to a better understanding of creativity is to unveil its underlying genetic architectures. Recently, several studies have been conducted to investigate the effects of dopamine (DA) and 5-hydroxytryptamine (5-HT) related genetic polymorphisms on creativity. Among DA related genes, dopamine D2 receptor gene(DRD2) is one of the most promising candidate genes for creativity. This study systematically explored the associations between DRD2 genetic polymorphisms and creative potential in the Han Chinese population. Fifteen single-nucleotide polymorphisms (SNPs) covering DRD2 were genotyped in 543 unrelated healthy Chinese undergraduate students whose creative potentials were assessed by divergent thinking (DT) tests. Single SNP analysis showed that, for verbal DT tests, 7 SNPs (rs4648319, rs2283265, rs1076560, rs6276, rs6279, rs6278, and rs1800497) showed significant associations with verbal fluency, and 2 SNPs (rs6277 and rs7122246) showed significant associations with verbal originality. For figural DT tests, 5 SNPs (rs2283265, rs6276, rs6279, rs6278 and rs1800497) showed significant associations with figural fluency, and 2 SNPs (rs6278 and rs1800497) showed significant associations with figural flexibility. Haplotype analysis showed that the 10-SNP haplotype consisting of rs4648319, rs4436578, rs7122246, rs2283265, rs1076560, rs6277, rs6276, rs6279, rs6278, and rs1800497 was significantly associated with verbal fluency. In conclusion, this exploratory study provides preliminary evidence for the involvement of DRD2in creative potential.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".