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Record W7038453412

Illinois Waterfowl Surveys and Investigations W-43-R-65-B Annual Progress Report FY2018

2018· article· en· W7038453412 on OpenAlexaboutno aff

Bibliographic record

VenueIDEALS (University of Illinois Urbana-Champaign) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceIllinois Department of Natural Resources
KeywordsFlywayWaterfowlPopulationFlockHabitatSpring (device)Range (aeronautics)Abundance (ecology)
DOInot available

Abstract

fetched live from OpenAlex

We monitored cellular-collared Canada geese in the Greater Chicago Metropolitan Area, specifically their use of space near Midway International Airport(MWD).Extensions of runways 13 and 31 were intersected more frequently (13.26% of transitional movements, x = 225) than extensions of runways 4 and 22 (2.52% of transitional movements, x = 76). We recorded 18 instances of movements intersecting airspace over runways at MDW (0.60% of transitional movements).The majority of transmittered Canada geese bred within the range of the temperate-nesting, Mississippi Flyway Giant Population with the exception of one male that appeared to be part of the subarctic-nesting, Mississippi Valley Population based on timing of migration and movement pattern indicating nesting. On average, 24.6% of transmittered geese underwent molt migrations during 2015–2017.We monitored the chronology and distribution of shorebirds aerially in the IRV during autumn and spring migration. Total number of shorebirds peaked in the IRV during autumn 2017 at 18,120, and averaged 12,024 birds/flight. We noted a positive trend with shorebird abundance and mudflat availability as river levels decreased in the IRV during August 2017. We documented lower shorebird numbers during spring 2018 in the IRV with a peak of 3,320 birds and an average of 2,527 birds/flight.Fluctuating water levels during migration drastically reduced the availability of shorebird habitat in the IRV during spring.Aerial detection of shorebird flocks was 97% and aerial count bias was 89.1% (range 0–250%) for total shorebirds. Count bias averaged 101.1% for large shorebirds and 80.4% for small shorebirds.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.006
Threshold uncertainty score1.000

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 studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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
Published2018
Admission routes1
Has abstractyes

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