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Record W7079658642 · doi:10.26108/3rh7-9s81

Fall migration decisions of northern saw-whet owls at an ecological barrier

2016· article· en· W7079658642 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2016
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsMainlandRange (aeronautics)Barrier islandMainland ChinaNocturnalGreat barrier reef

Abstract

fetched live from OpenAlex

Migration is a perilous undertaking for any organism, and is often only undertaken within a restricted range of intrinsic and extrinsic motivating factors. The added risk of crossing an ecological barrier such as a large body of water means that migratory decisions based on these factors become more crucial for survival than they would be otherwise. Aside from limited data garnered from banding-recapture studies, little was previously known about migratory habits of northern saw-whet owls (Aegolius acadicus), especially with respect to how they navigated large expanses of water such as the Gulf of Maine. Between 12 October 2015 and 10 November 2015, 26 saw-whet owls were captured at two NS sites using mist nets, banded, and fitted with very high frequency (VHF) radio-transmitters. Using data downloaded from receiver towers long the coastlines of Canada's Maritime Provinces and the northeastern United States, I tracked individual saw-whet owls as some moved throughout mainland NS, some remained in the same general area where they were originally tagged , and some migrated directly over the Gulf of Maine. The latter results provide insights into a previously unknown feat of migration by a small (80 to 120g) nocturnal raptor.

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)0.001
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 score0.359
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.241
Teacher spread0.219 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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