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Record W2775694727 · doi:10.1371/journal.pone.0189473

Maaqwi cascadensis: A large, marine diving bird (Avialae: Ornithurae) from the Upper Cretaceous of British Columbia, Canada

2017· article· en· W2775694727 on OpenAlexaffabout
Sandy McLachlan, Gary W. Kaiser, Nicholas R. Longrich

Bibliographic record

VenuePLoS ONE · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsUniversity of VictoriaRoyal British Columbia Museum
FundersBurke Museum, University of WashingtonUniversity of Washington
KeywordsCoracoidCretaceousPaleontologyBiologyGeography

Abstract

fetched live from OpenAlex

Mesozoic bird fossils from the Pacific Coast of North America are rare, but small numbers are known from the Late Cretaceous aged sediments of Hornby Island, British Columbia. Most are unassociated fragments that offer little information, but additional preparation of a large coracoid has revealed more details of its structure, as well as three associated wing bones. Phylogenetic analysis suggests that Maaqwi cascadensis, gen. et sp. nov. represents a derived crown or near-crown member of Ornithurae, and specifically suggests affinities with Vegaviidae. M. cascadensis is characterized by large size, and regressions based on dimensions of the coracoid suggest a large bird, with an estimated body mass of approximately 1.5 kilograms. The bones are robust, with thick walls, suggesting that M. cascadensis was a bird adapted for diving, similar to modern loons and grebes. The wings are short, while the coracoid is unusually short and broad, similar to modern loons. Along with the Ichthyornithes and Hesperornithes, M. cascadensis and Vegaviidae appear to represent a third clade of bird that evolved to exploit marine habitats in the Late Cretaceous, one specialized for foot-propelled diving and rapid cruising flight over water.

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 score0.437
Threshold uncertainty score0.879

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.181
Teacher spread0.163 · 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

Citations34
Published2017
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicPaleontology and Evolutionary BiologyFrench-language works237,207