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Record W2325742295 · doi:10.1061/41114(371)213

Improving Lake Superior Outflow Regulation—Phase 2 of the International Upper Great Lakes Study

2010· article· en· W2325742295 on OpenAlexaboutno aff
Anthony J. Eberhardt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDredgingGovernment (linguistics)Remedial educationWork (physics)Climate changeEnvironmental resource managementEnvironmental scienceHydrology (agriculture)OceanographyGeologyEngineeringPolitical science

Abstract

fetched live from OpenAlex

Over the last three years, hundreds of investigators from U.S. and Canadian government and non-government agencies and universities around the Great Lakes have been studying the possible factors responsible for recent declining upper Great Lakes levels. They have concluded that over the last four decades, the conveyance of the St. Clair River, the river connecting Lake Michigan-Huron to Lake Erie, has changed due to man-made factors like dredging but also due to natural factors like a major ice jam that occurred in 1984. However, they also determined that the declining lake levels were due primarily to climatic variability and glacial isostatic rebound. As such, remedial structural measures in the St. Clair River were not warranted. With that important phase of investigations ending, the International Upper Great Lakes Study (IUGLS) is shifting its focus to investigations toward formulating alternative plans for Lake Superior outflow regulation with the goal of providing benefits to existing and emerging interests. The Lake Superior Regulation Task Team has organized a team of performance indicator, integration and advisory technical work groups to formulate and evaluate alternatives to the present plan for Lake Superior regulation, Plan 1977-A, which has been in use since 1990. It already has been determined that improvements based on historic supplies will be small. However, considering more extreme conditions that could result under climate change-type scenarios, improvements may be identified, particularly when considering adaptive management. Connecting channel structural changes will also be considered. This paper describes the studies that are planned and the strategies that are being envisioned that will lead to alternative regulation plans by Study completion in the Spring of 2012.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.009
GPT teacher head0.235
Teacher spread0.226 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2010
Admission routes1
Has abstractyes

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