A Comparison between Local and Global Spaceborne Chlorophyll Indices in the St. Lawrence Estuary
Bibliographic record
Abstract
Spaceborne chlorophyll indices based on red fluorescence (wavelength = 680 nm) and water leaving radiance (Lw) in the visible spectrum (i.e., 400–700 nm) were evaluated in the St Lawrence Estuary (SLE) during September of 2011. Relationships between chlorophyll concentration (chl) and fluorescence were constructed based on fluorescence line height (FLH) measurements derived from a compact laser-based spectrofluorometer developed by ENEA (CASPER) and using spectral bands corresponding to the satellite sensor MERIS (MEdium Resolution Imaging Spectrometer). Chlorophyll concentration as estimated from CASPER (chlCASPER) was relatively high NE of the MTZ (upper Estuary), and nearby areas influenced by fronts or freshwater plumes derived from secondary rivers (lower estuary). These findings agree with historical shipboard measurements. In general, global chl products calculated from Lw had large biases (up to 27-fold overestimation and 50-fold underestimation) with respect to chlCASPER values. This was attributed to the smaller interference of detritus (mineral + organic non-living particulates) and chromophoric dissolved organic matter on chlCASPER estimates. We encourage the use of spectrofluorometry for developing and validating remote sensing models of chl in SLE waters and other coastal environments characterized by relatively low to moderate (<10 g·m−3) concentrations of detritus.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".