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Record W4383740458 · doi:10.1017/9781108938570

Ecology and Conservation of Mountain Birds

2023· book· en· W4383740458 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEcologyHabitatGeographyBiodiversityClimate changeRecreationConservation biologyBiology

Abstract

fetched live from OpenAlex

High mountain habitats are globally important for biodiversity. At least 12% of birds worldwide breed at or above the treeline, many of which are endemic species or species of conservation concern. However, due to the challenges of studying mountain birds in difficult-to-access habitats, little is known about their status and trends. This book provides the first global review of the ecology, evolution, life history and conservation of high mountain birds, including comprehensive coverage of their key habitats across global mountain regions, assessments of diversity patterns along elevation gradients, and adaptations for life in the alpine zone. The main threats to mountain bird populations are also identified, including climate change, human land use and recreational activities. Written for ecologists and naturalists, this book identifies key knowledge gaps and clearly establishes the research priorities needed to increase our understanding of the ecology of mountain birds and to aid in their conservation.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score0.716

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.189
Teacher spread0.170 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations17
Published2023
Admission routes1
Has abstractyes

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