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Record W3001401725 · doi:10.54119/jaas.2019.7324

Long-tailed Weasel (Mustela frenata) Distribution Survey in Arkansas: Challenges in Detecting a Rare Species

2019· article· en· W3001401725 on OpenAlexaboutno aff
Suzanne D Johnston, D. Sasse, Robert Kissell

Bibliographic record

VenueJournal of the Arkansas Academy of Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsEcoregionWeaselGeographyMustelidaeOccupancyEcologyDistribution (mathematics)Species distributionSampling (signal processing)Physical geographyHabitatBiologyPredation

Abstract

fetched live from OpenAlex

Long-tailed weasels (Mustela frenata) have one of the widest distributions of mustelids in the western hemisphere and were distributed across a majority of the American continents ranging from Canada through the contiguous United States, Mexico, and into northern South America. However, on a local scale they are considered uncommon and rare. We assessed the distribution of long-tailed weasels across Arkansas to determine occupancy in each ecoregion of Arkansas, and determined the detectability on two local, adjacent sites. No long-tailed weasels were detected within the ecoregions, but the species was detected with intensive sampling on one local site. It should be emphasized that although the species was not detected within the ecoregions, this does not indicate it does not occur broadly across the state.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.250
Teacher spread0.210 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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