Optical characteristics of cryoconite (surface dust) on glaciers: the relationship between light absorbency and the property of organic matter contained in the cryoconite
Bibliographic record
Abstract
Abstract Optical characteristics of the cryoconite collected from nine glaciers in the Himalaya, Tibet and the Arctic (Canada and Svalbard) were analyzed. The spectral light reflectance (visible region) of the cryoconite on the six glaciers in the Arctic and the Himalayawas generally low, indicating high light absorbency (dark coloration) of the cryoconite. In contrast, the spectral reflectances of the cryoconite on the three glaciers in Tibet were significantly higher than on the other glaciers. There was no significant difference in the spectral reflectance of mineral particles contained in the cryoconite between the Tibetan and the other glaciers, indicating that the difference in the albedo of the cryoconites is not due to the mineral particles, but due to organic matter contained in the cryoconite. Chemical analysis of the organic matter in the cryoconites revealed that the light absorbency of cryoconites is due to the amount of humic substances, which are dark-colored organic substances, the residue of bacterial decomposition of organic matter. The cryoconite of the three glaciers in Tibet contained significantly smaller amounts of humic substances than that of the other glaciers, probably due to different biological or chemical conditions. Results show that the formation of the humic substances in the cryoconite affects its optical characteristics, and possibly affects the surface albedo of the glaciers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".