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Record W2014898945 · doi:10.3996/042012-jfwm-034

Effect of Weekly Hunting Frequency on Duck Abundances in Mississippi Wildlife Management Areas

2013· article· en· W2014898945 on OpenAlexaff
Elizabeth A. James, Michael L. Schummer, Richard M. Kaminski, Edward J. Penny, L. Wes Burger

Bibliographic record

VenueJournal of Fish and Wildlife Management · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsBirds Canada
Fundersnot available
KeywordsWaterfowlAnasWildlifeWildlife managementAbundance (ecology)GeographyHabitatWildlife refugeWildlife conservationEcologyFisheryBiology

Abstract

fetched live from OpenAlex

Abstract Management of waterfowl habitat and hunting frequency is important to sustain hunting opportunities in Mississippi and elsewhere in North America. Managers have limited scientific information regarding the effect of weekly hunting frequency on waterfowl abundance for use in developing hunting plans for public hunting areas. We divided the hunted portions of three Mississippi Wildlife Management Areas into two treatments to evaluate the effect of hunting 2 versus 4 d/wk on duck abundance. Abundance of all ducks, mallard Anas platyrhynchos, northern shoveler Anas clypeata, and green-winged teal Anas crecca were not detectably different between weekly hunting frequencies. Sanctuary use increased approximately 30% during the first 1.25 h after sunrise regardless of hunting disturbance being present or absent. Our results indicate that duck abundance did not increase with increased rest days at Wildlife Management Areas, suggesting these areas may be hunted 4 d/wk without significantly decreasing duck abundance. Sanctuaries were used daily and may be vital to attract and retain ducks on Wildlife Management Areas.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.147
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations26
Published2013
Admission routes1
Has abstractyes

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