Changing Views of Arctic Protists (Marine Microbial Eukaryotes) in a Changing Arctic
Bibliographic record
Abstract
Abstract. Advances in sequencing technology and the environmental genomic approaches have brought attention to the vastness of protist biodiversity. While over much of the world’s oceans the species and phylotypes making up this diversity are assumed to be something previously hidden and now revealed, the recent rapid changes in the Arctic mean that such assumptions may be a simplification. Historical morphological species data can be used to validate new records provided that more of these species are identified using standard molecular markers. Environmental surveys can also go further by identifying species over regions, seasons and depths. High throughput sequencing and bioinformatics tools provide a means of monitoring and eventually predicting the consequences of change. We give an example of how microbial eukaryote communities differ over pan-arctic scales, emphasizing the need for additional sampling and the need for caution in extrapolating the results of one region to the entire Arctic.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".