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Record W6986944716

Rogue River Watershed Project / Rogue River Watershed Management Plan

2000· article· en· W6986944716 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks - GVSU (Grand Valley State University) · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTributaryWatershedWatershed managementHydrology (agriculture)Water resourcesMain riverLand use
DOInot available

Abstract

fetched live from OpenAlex

The Rogue River is located in west central lower Michigan and is a major tributary of the Grand River. The Rogue River Watershed refers to all the land that is drained by the Rogue River. This area is 167,625 acres and includes portions of Kent, Montcalm, Muskegon, Newaygo, and Ottawa counties. The City of Rockford and Cedar Springs, and the villages of Sparta, Kent City, Sand Lake, and Casnovia are within the Rogue River Watershed boundaries. The Rogue River is fed by wetlands, county drains, lakes, and both warm and cool-cold water tributaries. The cool-cold water tributaries help to sustain trout and other cool-cold water species in the southern section of the Rogue River. The land use in the southern section of the watershed is urban and rural areas with pastureland, upland crops, and forestland. Muckland crops dominate the northern part of the watershed. Changes in land use from rural to urban have created concern for the Rogue River Watershed. This concern was addressed January 1, 1999 with the partnership between Grand Valley Metro Council and the Annis Water Resources Institute to create a watershed management plan for the Rogue River Watershed.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score0.167

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 studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.006

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 head0.030
GPT teacher head0.207
Teacher spread0.177 · 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 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

Citations0
Published2000
Admission routes1
Has abstractyes

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