Biological characteristics of dark colored material (cryoconite) on Canadian Arctic glaciers (Devon and Penny ice caps) (scientific paper)
Bibliographic record
Abstract
Biological characteristics of dark colored material (cryoconite) collected from Canadian Arctic glaciers (Devon and Penny ice caps) are described. The cryoconite consists of mineral particles and organic matter. The amount of organic matter was 0.8-13.8% dry weight. Seven taxa of snow algae (Chlorophyta and Cyanophyta) were observed in the cryoconite. The mineral particles, the algae, the bacteria, and amorphous organic matter formed small dark colored granules (cryoconite granules). The size of the granules was approximately 0.4mm in diameter. Microscopy of the granules revealed that the granules contain bacteria with mucus like substance, and that the surface of the granules was covered with filamentous blue-green algae. These observations suggest that the granules are formed by algal and bacterial activity on the glaciers, and that the cryoconite includes a large amount of biological products. The amount of the cryoconite per unit area on the glacier surface was generally small (mean 48g m^<-2> in dry weight). In contrast, a large amount of the cryoconite was deposited at the bottom of cryoconite holes. The small amount of cryoconite on the glacier surface means that the effect of the cryoconite on albedo reduction of the glacier surface is small.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 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".