Prevalence of cilantro (Coriandrum sativum) disliking among different ethnocultural groups
Bibliographic record
Abstract
Cilantro, the leaf of the Coriandrum sativum plant, is an herb that is widely consumed globally and has purported health benefits ranging from antibacterial to anticancer activities. Some individuals report an extreme dislike for cilantro, and this may explain the different cilantro consumption habits between populations. However, the prevalence of cilantro dislike has not previously been reported in any population. The objective of this study was to determine the prevalence of cilantro dislike among different ethnocultural groups from a population of young adults living in Canada. Subjects (n = 1,639) between the ages of 20 and 29 years were participants of the Toronto Nutrigenomics and Health Study. Individuals rated their preference for cilantro on a 9-point scale from ‘dislike extremely’ to ‘like extremely’. Subjects also had the option to select ‘have not tried’ or ‘would not try’. Subjects who selected 1 to 4 were classified as disliking cilantro. The prevalence of dislike ranged from 3 to 21%. The proportion of subjects classified as disliking cilantro was 21% for East Asians, 17% for Caucasians, 14% for those of African descent, 7% for South Asians, 4% for Hispanics, and 3% for Middle Eastern subjects. These findings show that the prevalence of cilantro dislike differs widely between various ethnocultural groups.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".