Hydrodynamic control of the underwater light climate in fluvial Lac Saint‐Pierre
Bibliographic record
Abstract
We measured characteristics of the underwater light spectra (e.g., attenuation of ultraviolet [UV] radiation, photosynthetically active radiation) and select dissolved and particulate physicochemical properties (e.g., chromophoric dissolved organic carbon [CDOM], dissolved and particulate organic carbon, inorganic dry weights, beam attenuation coefficients, particulate absorption coefficients, and nutrients) in different water masses of fluvial Lac Saint‐Pierre (Canada). We used these variables as tracers to reveal the extent and magnitude of spatial and temporal heterogeneity in this large, shallow, fluvial lake of the St. Lawrence River. We superimposed these tracer variables over radiance data obtained from satellite images to identify spatial and temporal changes in the distribution of different water masses and their bio‐optical components. The underwater light environment showed strong horizontal (longitudinal and lateral) variability because of the strong connectivity between the terrestrial and aquatic environments in the lake’s tributaries and adjoining wetlands. Analyzing the downstream distribution of optical and chemical variables as a function of transport time rather than distance from source tributaries allowed us to demonstrate large differences in the age of the different water masses depending on the characteristics of the source tributary, in‐stream processes, and distance from its source. CDOM explained most of the UV attenuation and allowed the greatest discrimination between water masses.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".