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Record W2910132188

Missouri Department Of Natural Resources Wild Areas (2010)

2016· dataset· en· W2910132188 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationNatural resourceWildernessGeographyWilderness areaNatural (archaeology)ButteGeological surveyOrthophotoBoundary (topology)Quarter (Canadian coin)LandformEnvironmental resource managementArchaeologyEnvironmental planningCartographyEcologyEnvironmental scienceRemote sensingGeology
DOInot available

Abstract

fetched live from OpenAlex

this data set depicts the boundaries of wild areas managed by the missouri department of natural resources division of state parks this data was derived by digitizing united states geological survey usgs digital orthophoto quarter quadrangles doqq from boundary descriptions and sketches varying in age content and quality the missouri wild area system was partially modeled after the national wilderness preservation system wild areas are protected by the benefits they provide for hiking and backpacking as well as the benefits they provide as outdoor classrooms for environmental education and as increasingly important reservoirs of scientific information according to the department of natural resources policy a wild area must be a spacious tract of land generally 1 000 or more acres in size generally it must appear to have been affected primarily by the forces of nature and to possess outstanding opportunities for solitude and unconfined recreation

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)0.004
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.198
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.011
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.042

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 head0.024
GPT teacher head0.219
Teacher spread0.196 · 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
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

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Same topicBotany, Ecology, and Taxonomy StudiesFrench-language works237,207