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Record W404415983

Land Cover Classification of Bass River Recreation Area, Ottawa Co., Michigan

2013· article· en· W404415983 on OpenAlexaboutno aff
Nicholas Barlow

Bibliographic record

VenueScholarWorks - GVSU (Grand Valley State University) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationGeographyBass (fish)Land coverCover (algebra)FisheryForestryEnvironmental scienceHydrology (agriculture)Land useEngineeringPolitical scienceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

Bass River Recreation Area is a state recreation area located along the Grand River in Ottawa County, Michigan. Bass River comprises 1,665 acres comprised of open brush land, ponds, man-made lakes and forest. The Michigan Department of Natural Resources (MDNR) manages the area for recreation and wildlife. Currently, there are no existing forest inventory datasets or comprehensive land cover maps. A land cover classification will aid the MDNR in establishing a natural features inventory for Bass River. We will utilize ERDAS Imagine to classify land cover types by combining supervised and unsupervised classification methods from aerial imagery acquired in August 2010 by the National Agriculture Imagery Program. The resulting integrated land cover classification will provide the state with a current, spatially-explicit inventory of land cover and will assist the MDNR in future management decisions at Bass River Recreation Area.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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 teacher head, not a consensus.

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
Published2013
Admission routes1
Has abstractyes

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