Identifying fossil wild rice (Zizania) pollen from Cootes Paradise, Ontario: a new approach using scanning electron microscopy
Bibliographic record
Abstract
Although prehistoric native peoples probably used wild rice for food and ceremony, evidence is sparse. Macrofossil remains of wild rice are uncommon on archaeological sites even where the plant is still common nearby. The association between documented human habitation and wild rice is explored with pollen records from associated wild rice wetlands. For this, reliable identification of wild rice pollen is essential. Three approaches are examined: (1) the pollen spectral signature (percentage and density of grass pollen), (2) coeval community pollen types, and (3) the pollen morphology (size and sculpturing) of wild rice versus other stand-forming wetland grasses. We report pollen spectra from a contemporary wild rice marsh and compare it with fossil pollen from Cootes Paradise, a wetland at the western end of Lake Ontario. The pollen signature from the modern wild rice wetlands was similar to that of the fossil site, but this correspondence does not confirm that the fossil grass pollen is wild rice. Wild rice pollen is separable by size from that of all the stand-forming wetland grasses examined, but the fossil pollen from Bull’s Point is not the same size as that of modern wild rice. Scanning electron microscopy (SEM), however, indicates that wild rice pollen is identifiable by its sculpturing and that the fossil pollen has an identical micromorphology. 2003 Published by Elsevier Ltd.
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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 | 0.000 |
| 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 | 0.000 |
| 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".