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Record W2114210366 · doi:10.1080/02724634.2014.948546

Four new Early Devonian ischnacanthid acanthodians from the Mackenzie Mountains, Northwest Territories, Canada: an early experiment in dental diversity

2015· article· en· W2114210366 on OpenAlexafffundabout
S. Blais, Chelsea R. Hermus, Mark V. H. Wilson

Bibliographic record

VenueJournal of Vertebrate Paleontology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsDevonianDentitionBiologyPaleontologyEcologyZoologyGeography

Abstract

fetched live from OpenAlex

The Early Devonian (Lochkovian) Man On The Hill (MOTH) locality in the Northwest Territories has yielded hundreds of exquisitely preserved specimens of over 72 different species of early vertebrates, greatly increasing our understanding of the diversity of this period. In this paper, we describe three new genera comprising four new species of ischnacanthid acanthodian, based on their dentigerous jaw bones and teeth. This taxonomic diversity reflects some of the diversity of dentition found among ischnacanthiform acanthodians at the MOTH locality, in contrast to their highly conservative body forms. This high diversity of related forms suggests an early radiation in jaw and tooth morphology in Early Devonian ischnacanthiform acanthodians in this region. All ischnacanthiform specimens from MOTH were originally assigned to Ischnacanthus gracilis. However, study of the unique jaw and tooth morphology of MOTH ischnacanthiform specimens indicates that it is unlikely that Ischnacanthus was present at the MOTH locality.http://zoobank.org/urn:lsid:zoobank.org:pub:73D3F772-0354-4AB4-9956-ECE0A2431A05

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 score0.317
Threshold uncertainty score0.637

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.238
Teacher spread0.197 · 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

Citations14
Published2015
Admission routes3
Has abstractyes

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