Lake Erie Satellite-derived Annual Algal Bloom Indices
Bibliographic record
Abstract
This dataset contains annual algal bloom indices (duration, extent, intensity, severity) summary statistics (maximum, mean) over the June through October monitoring period for Lake Erie. These data are derived from satellite remote sensing algorithms using European Space Agency's (ESA's) MEdium Resolution Imaging Spectrometer (MERIS) sensor on the Envisat satellite (2002-2012) and ESA's Ocean and Land Colour Instrument (OLCI) sensor on the Sentinel 3A and Sentinel 3B satellites (2016-present). At the end of each monitoring season, data are presented in annual report format including current and historical summary statistics of algal bloom indices, alongside relevant imagery. Citation: Binding, C.E., Pizzolato, L., & Zeng, C. (2021). EOLakeWatch; delivering a comprehensive suite of remote sensing algal bloom indices for enhanced monitoring of Canadian eutrophic lakes. Ecological Indicators, 121, 106999. doi:10.1016/j.ecolind.2020.106999
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.012 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.213 |
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; both teacher heads agree on what is shown here.
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".