Record-Breaking Lake Erie Hypoxia during 2012 Drought
Bibliographic record
Abstract
Hypoxia has been observed in the central basin of Lake Erie for decades. To understand the impact of various controlling factors, we analyze a record of hypoxic extents for Lake Erie for 1985–2012 and develop a parsimonious model of their interannual variability. We find that the 2012 North American drought and accompanying low tributary discharge was associated with a record-breaking hypoxic event in Lake Erie, whereas a record-setting harmful algal bloom in 2011 was likely associated with only mild hypoxia. River discharge and the timing of nutrient input therefore impact western basin bloom growth and central basin oxygen demand in distinct ways that merit further investigation. Overall, April to June tributary discharge, May to July soluble reactive phosphorus loading, July wind stress, and June northwesterly wind duration explain 82% of the interannual variability of hypoxia, and discharge alone explains 39%, indicating that meteorological factors need to be considered in the development of nutrient management strategies, especially as both extreme precipitation events and droughts become more frequent under a changing climate.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".