Bibliographic record
Abstract
2 The patterns of seasonal variation of surface plant pigment concentration (Chl) in the Newfoundland Region were studied using the remo ely sensed data from CZCS (1978–1986) and SeaWiFS radiometers (fromSeptember 1997 to October 1999). Sea Surface Temperature (SST) data obtained from AVHRR radiometers and Sea Surface Height (SSH) data obtained from TOPEX/POSEIDON altimeter were used then to interprete the observed patterns in terms of physical factors which influence the growth of phytoplankton. Stable seasonal cycles of both SST and Chl were observed in all parts of the region under study (Labrador Current, Newfoundland Bank, Flemish Pass, frontal zone between Gulf Stream and Labrador Current). The SST values in summer season during two years under study (September 1997–October 1999) were up to 3°C higher as compared with climatically averaged values. The seasonal pattern of Chl in Labrador Current zone was typical of Arctic regions (one maximum in summer), in Gulf Stream zone it was typical of subtropical regions (smoothed maximum during winter), and in between these zones it was typical of mid-latitudes (two maxima in spring and autumn). Over the Grand Newfoundland Bank the seasonal pattern had one spring m ximum, typical of shallow regions. The patterns of seasonal phytoplankton cycles resulted mainly from the meteorological factors influencing water stratification; the latter seems to be a crucial factor in either light or nutrient limitation of phytoplankton growth. 3 1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.754 | 0.578 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".