Exaggerated expectations in ancient starch research and the need for new taphonomic and authenticity criteria
Bibliographic record
Abstract
Ancient starch research illuminates aspects of human ecology and economic botany that drove human evolution and cultural complexity over time, with a special emphasis on past technology, diet, health, and adaptation to changing environments and socio-economic systems. However, lapses in prevailing starch research demonstrate the exaggerated expectations for the field that have been generated over the last few decades. This includes an absence of explanation for the millennial-scale survivability of a biochemically degradable polymer, and difficulties in establishing authenticity and taxonomic identification. This paper outlines new taphonomic and authenticity criteria to guide future work toward designing research programs that fully exploit the potential of ancient starch while considering growing demands from readers, editors, and reviewers that look for objective compositional identification of putatively ancient starch granules.
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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 | 0.181 | 0.251 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.005 | 0.071 |
| Scholarly communication | 0.020 | 0.034 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 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".