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Record W2055107430 · doi:10.1080/07900620600807771

Sustainable Groundwater Allocation in the Great Lakes Basin

2006· article· en· W2055107430 on OpenAlexaff
Timothy Morris, Satya P. Mohapatra, Anne Mitchell

Bibliographic record

VenueInternational Journal of Water Resources Development · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsCanadian Institute for Health InformationCanadian Institute for Advanced ResearchUniversity of British Columbia
Fundersnot available
KeywordsGroundwaterWatershedStructural basinWater resource managementWatershed managementEnvironmental planningEnvironmental resource managementEnvironmental scienceComputer scienceGeology

Abstract

fetched live from OpenAlex

Outdated groundwater allocation policies have resulted in unrestrained abstraction of groundwater in the Great Lakes Basin. Continuing on this course will lead to more frequent conflicts and further degradation of the Basin's ecosystem. Alternative approaches must focus on achieving sustainable groundwater allocation. The authors present two alternative institutions, local collaborative planning for groundwater allocation, and a regional watershed board. Collaborative institutions responsible for local groundwater planning should be established according to practical geographical units, have access to sound scientific information, utilize adaptive management and engage in open deliberation. The regional watershed board should establish a comprehensive and unified inventory of all groundwater resources in the Basin, designate critical groundwater areas, monitor groundwater management by respective jurisdictions, and make recommendations on best practices.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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