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Record W2761065694 · doi:10.1177/0309133317734103

Whale geography

2017· article· en· W2761065694 on OpenAlexaff
Rianna E. Burnham

Bibliographic record

VenueProgress in Physical Geography Earth and Environment · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEcologyHabitatGeographyWhaleAbundance (ecology)BiogeographyNicheOrganismSpecies distributionDistribution (mathematics)PopulationSoundscapeSound (geography)BiologyOceanographyGeology

Abstract

fetched live from OpenAlex

Typically, organism-based biogeographic studies consider distribution and abundance over time on various scales. However, to be comprehensive, factors of environment and habitat, energetics, morphology, and population dynamics should also be included. In addition, these studies should consider not only the spatial extent that an individual or species occupies or can roam within, but also the space over which an animal can extract and interpret information, a less well-defined element of niche space which largely shapes its movements or distribution. Understanding the processes that inform patterns of species distribution, both intrinsic and external to the animal, is key to understanding a species’ ecology. Here, we consider the biogeography of whales, given these ideas, with a particular focus on the acoustical components of their biology and landscape. Cetaceans use of sound to communicate, navigate and forage, and so interpret the soundscape, is a central consideration. It has important implications in a changing ambient environment and will increasingly influence species’ survival.

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 score0.263
Threshold uncertainty score0.850

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 head0.010
GPT teacher head0.229
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

Citations10
Published2017
Admission routes1
Has abstractyes

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