Relationships between spectral optical properties and optically active substances in a clear oligotrophic lake
Bibliographic record
Abstract
The absorption and scattering coefficients in the euphotic zone of oligotrophic Lake Taupo, New Zealand, were measured at 19 stations across the 620 km2 lake in late fall during the period of mixed layer deepening and development of the annual phytoplankton maximum. These coefficients were subsequently related to the water content of colored dissolved organic matter (CDOM), phytoplankton, and nonalgal particles via measurements of the absorption spectra of these optically active substances and of chlorophyll a and suspended particle concentrations. Measurements of the spectral diffuse attenuation coefficient for downwelling irradiance (Kd) and of reflectance (Lu/Ed) revealed that the clear blue waters of Lake Taupo had a minimum Kd of 0.09 m−1 at 500 nm and maximum reflectance at 490 nm. The measured Kd and Lu/Ed were well described by modeled spectra that were computed using a radiative transfer model (Hydrolight) assuming relatively low values for the backscattering ratio (0.008–0.014). The relationships established here between the optical properties and optically active substances were consistent with previous observations in case 2 marine waters, and they will provide a basis for prediction of eutrophication, climate, and other environmental effects on the blueness and transparency of large oligotrophic lakes.
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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) | 0.000 | 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) | 0.000 | 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".