Effects of water color on underwater irradiance and consequences for photosynthetic pigments of primary producers in boreal lakes
Bibliographic record
Abstract
Photosynthetic pigment contents of phytoplankton and macrophytes ( Nuphar lutea) were studied along a water color gradient of lakes. Chlorophyll a concentration in the water was affected by species composition of phytoplankton and the highest values were observed at intermediate color. Chlorophyll b concentration and chlorophyll b:biomass ratio of phytoplankton increased together with water color. The highest chlorophyll a: b ratios occurred at intermediate water color, because phytoplankton species with chlorophyll b were scarce. In N. lutea, chlorophyll a and b in the petioles were not affected by water color or light attenuation. For chlorophyll a: b of N. lutea the effect of water color was stronger than the effect of any light wavelength band. This was probably because the floating leaves have a strong effect on the light spectrum underneath the leaves. Chlorophyll a: b decreased moderately with increasing water color. Hence, the chlorophyll a: b ratio of N. lutea is a possible indicator of lake browning. For phytoplankton, variation in species composition complicates the use of chlorophyll a: b, but the chlorophyll b:biomass ratio is a possible indicator.
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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 | 0.000 | 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 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".