Plant Diversity in the Human Diet: Weak Phylogenetic Signal Indicates Breadth
Bibliographic record
Abstract
Worldwide, humans have access to a greater range of food plants than does any other species. Examination of phylogenetic patterns in plants consumed by animals has recently uncovered important ecological processes. The same techniques, however, have not been applied to our own species. Here we show that although humans tend to eat more species in certain families (e.g., Rosaceae) and fewer in others (e.g., Orchidaceae), the proportion of edible species in most families is similar to random expectations. Phylogenetic patterning in angiosperm edibility is also weak. We argue that the remarkable breadth of the human diet is the result of humans' huge geographic range, diverse food-collection methods, and ability to process normally inedible items. Humans are thus generalist feeders in the broadest sense. Cross-cultural analyses of diversity in the plant diet of humans could represent a fascinating new field of research linking ecology, anthropology, history, and sociology.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".