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Record W1552059705 · doi:10.5860/choice.45-4382

Owls of the United States and Canada: a complete guide to their biology and behavior

2008· article· en· W1552059705 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGenealogyBiologyGeographyHistory

Abstract

fetched live from OpenAlex

There is no group of birds more mysterious and fascinating than owls. The loudmouths of the raptor world, they peep, trill, toot, bark, growl, shriek, whistle, chittle, whoop, chuckle, boom, and buzz. Indeed, very few actually hoot. They have become the stuff of lore and legend-from the Roman myth that an owl foot could reveal secrets to the First Nations belief that an owl feather could give a newborn better night vision. But the truth about owls is much more exciting. In this gorgeous book, celebrated natural history writer and wildlife photographer Wayne Lynch reveals the secrets of this elusive species with stunning photographs, personal anecdotes, and accessible science. The photos alone are masterpieces. Unlike most published owl photos, which are portraits of birds in captivity, the vast majority of these were taken in the wild-a product of the author-photographer's incredible knowledge and patience. Lynch complements the photos with a wealth of facts about anatomy, habitat, diet, and family life. For each of the nineteen species that inhabit Canada and the United States, he provides a range map and a brief discussion of its distribution, population size, and status. Lynch debunks myths about owls' supernatural powers of sight and hearing, discusses courtship rituals, and offers personal tips for finding owls in the wild. From the great horned to the tiny elf owl, this amazing volume captures the beauty and mystery of these charismatic birds of prey.

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)0.000
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 score0.799
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.087
GPT teacher head0.291
Teacher spread0.204 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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