The Areal Characteristics of Chlorophyll α Distribution in the Sediments and Seawater in the Surveyed Area, Arctic Ocean
Bibliographic record
Abstract
Investigations of chlorophyll α was carried out in the seawater and sediment in the Chukchi Sea, Chukchi Plateau, the Slop-flow area, the Mendeleev Ride and the Canada Basin during the 2nd Chinese National Arctic Research Expedition in the summer of 2003. The results showed that chlorophyll α concentrations were 0.002~39.008 μg/dm3 at the surveyed waters; the surface chlorophyll α concentrations were 0.037~4.644 μg/dm3 and the average value was 0.612 μg/dm3 in the surveyed area. Chlorophyll α concentrations at the depths 20~30 m of the subsurface water were higher than that in the surface and under layer. Chlorophyll α concentration distribution was obviously areal characteristics. The areal arrange order of the water-column chlorophyll α concentration is the Chukchi Sea the Slop-flow area the Chukchi Plateau the Canada Basin the Mendeleev Ride. Chlorophyll α concentrations were 0~3.978 μg/g (wet mug) in the sediment of the surveyed stations; and the average value was 0.934 μg/g(wet mug) in 7 surveyed stations. Chlorophyll α concentrations at the surface sediments were higher than that in the under-layer. The areal arrange order of the sediments chlorophyll α concentration is the Chukchi Sea the Slop-flow area the Mendeleev Ride, and chlorophyll α concentration can not be examined in the sediments of the Chukchi Plateau and the Canada Basin.
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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 | 0.000 |
| 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 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".