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Record W2590101813 · doi:10.1111/jbi.12969

Conceptual and analytical worldviews shape differences about global avian biogeography

2017· article· en· W2590101813 on OpenAlexaff
Joël Cracraft, Santiago Claramunt

Bibliographic record

VenueJournal of Biogeography · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsRoyal Ontario Museum
FundersNational Science Foundation
KeywordsBiogeographyFossil RecordPaleontologyEcologyGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Abstract In a recent paper, we generated a new time tree of modern birds and integrated it with biogeographic and palaeontological information to formulate a model for their biogeographic history. We postulated that modern birds originated in West Gondwanan continents, from where they dispersed around the world. Mayr suggested that our selective use of the fossil record may have biased our ancestral area reconstructions. We argue that the use of the fossil record must be selective in order to avoid the influence of its severe geographic bias: rock formations with numerous high‐quality fossil birds are found only in North America and Europe. An indiscriminate use of the avian fossil record would bias any biogeographic analysis towards these two continents. Our biogeographic model is perfectly consistent with the existence of diverse fossil avifaunas in the Eocene of North America and Europe because dispersion out of South America occurred earlier, in the Palaeocene.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.007
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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 designTheoretical or conceptual
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

Citations14
Published2017
Admission routes1
Has abstractyes

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