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Record W2946470425

Breeding Diet of Northern Saw-whet Owls (Aegolius acadicus) in Central Alberta

2017· article· en· W2946470425 on OpenAlexaffabout
Emily Dowdall

Bibliographic record

VenueStudent Research Proceedings · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMacEwan University
Fundersnot available
KeywordsPelletBiologyPredationDentitionGeographyZoologyEcology
DOInot available

Abstract

fetched live from OpenAlex

Northern Saw-whet owl (Aegolius acadicus) nest box pellet pads were collected from Beaverhill Bird Observatory between the years 2004 and 2010. Due to the work of previous individuals, 18 of 36 pellet pads that were collected have been thoroughly dissected and analyzed for skeletal remains of prey species. The purpose of this study was to continue with the dissection of the remaining pellet pads and to identify the small mammals to the most specific taxonomic level possible based on the dentition. Identification keys were used to compare and identify the cranial elements of the small prey mammals found in the pellet pad and the minimum number of individuals (MNI) was also calculated by counting the number of right and left femur bones collected. The data collected from this study is important for gaining more insight into this mysterious yet abundant owl and to also detect if the diet of the saw-whet owl can change in response to a change in the ecosystem when compared to other pellet pads in varying landscapes. Discipline: Biology Faculty Mentor: Mark Degner

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.368
Threshold uncertainty score0.741

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.065
GPT teacher head0.371
Teacher spread0.305 · 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 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
Published2017
Admission routes2
Has abstractyes

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