Selection for Oil Content During Soybean Domestication Revealed by X-Ray Tomography of Ancient Beans
Bibliographic record
Abstract
When and under what circumstances domestication related traits evolved in soybean (Glycine max) is not well understood. Seed size has been a focus of archaeological attention because increased soybean seed weight/size is a trait that distinguishes most modern soybeans from their ancestors; however, archaeological seed size analysis has had limited success. Modern domesticated soybean has a significantly higher oil content than its wild counterpart so oil content is potentially a source of new insight into soybean domestication. We investigated soybean oil content using X-ray computed tomography (CT; specifically, synchrotron radiation X-ray CT or SRX-CT) of charred, archaeological soybean seeds. CT identified holes in the specimens that are associated with oil content. A high oil content facilitates the development of small holes, whereas a high protein content results in larger holes. The volume of small holes increased slowly from 7,500 to 4,000 cal B.P. We infer that human selection for higher oil content began as early as 7,500 cal B.P. and that high oil content cultivars were well established by 4,000 cal B.P.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".