Covariation among Alaskan chrysophyte stomatocyst assemblages and environmental gradients: A comparison with diatom assemblages
Bibliographic record
Abstract
Northern lakes, for which we have little long‐term data, are predicted to experience profound impacts with greenhouse warming. In order to assess the usefulness of chrysophytes as paleoenvironmental indicators, stomatocysts were enumerated from the surface sediments of 51 Alaskan lakes distributed along a strong climatic gradient. A total of 142 cyst morphotypes were described using light microscopy, of which 13 are believed to be new forms. Principal components analysis of the stomatocyst assemblages showed a limited amount of variation (Λ 1 = 0.11, Λ 2 = 0.09). However, redundancy analysis identified total phosphorus (TP), sodium (Na), and altitude (ALT) as significant variables in terms of their ability to describe the distribution of stomatocysts. Major ion and nutrient concentrations were also found to be strong predictors of diatom variation from the same lake set. In comparison to the diatom assemblages from the same lakes, the cysts were less abundant and showed a lower amount of species variation. Reasons for the lack of variation may be due to the predominance of unornamented and collective category cysts (i. e. cysts which cannot be differentiated under the light microscope).
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".