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Lake Erie: Past, Present, and Future

2019· other· en· W2982431887 on OpenAlexaboutno aff
Jeffrey M. Reutter

Bibliographic record

VenueEncyclopedia of Water · 2019
Typeother
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsOverfishingZebra musselWater qualityEnvironmental scienceFisheryDreissenaProductivityClimate changeFish killEnvironmental protectionOceanographyEcologyNutrientFish <Actinopterygii>Algal bloomMusselGeology

Abstract

fetched live from OpenAlex

Abstract Lake Erie is the southernmost, shallowest, warmest, most nutrient enriched, and biologically the most productive of the Great Lakes. The degradation of the Lake's water quality and the burning of the Cuyahoga River in the 1960s and 1970s made it the poster child for pollution problems in the world and paved the way for the Great Lakes Water Quality Agreement, the formation of USEPA, NOAA, and Environment and Climate Change Canada, the first Earth Day, and the passage of the Clean Water Act. A long history of overfishing led to the creation of the Great Lakes Fishery Commission and its highly successful interagency quota management system. The lake's extreme productivity and poor management allowed the zebra mussel and many other aquatic invasive species to enter and thrive. Good management in the 1970s and 1980s restored water quality and allowed the lake to become the Walleye Capital of the World. Today excessive nutrient loading has returned and many of the problems of the 1970s are back. The challenges are great and the solutions are different, but the lake is resilient and if we have the political resolve, it can be brought back again.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.211
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2190.008

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.

Opus teacher head0.004
GPT teacher head0.200
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations19
Published2019
Admission routes1
Has abstractyes

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