Chlorophyll-a and Salinity Concentrations Derived from Satellite Images for the Estuary and Gulf of St. Lawrence (1998-2023)
Bibliographic record
Abstract
This dataset presents the result of a model developed to retrieve chlorophyll-a (chla) and salinity concentrations from various satellites in the St. Lawrence Estuary and Gulf. This version replaces the previous ones, with estimates derived from a retuning of the model based on additional in situ and satellite-derived data. The input data is now exclusively from the European Space Agency's Ocean Color Climate Change Initiative (CCI) program. The ocean color, seen from space, makes it possible to estimate the chlorophyll content in water. This pigment is an index of the biomass of microscopic algae. Compared to the Atlantic Ocean, the waters of the Estuary and Gulf of St. Lawrence are rather isolated and are highly mixed with fresh water from numerous rivers. This dataset is produced as part of the Coastal Environmental Baseline Program under Fisheries and Oceans Canada's Oceans Protection Plan.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.024 |
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".