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Record W2128901068 · doi:10.1111/pala.12168

The macro‐ and microfossil record of the Cambrian priapulid <i>Ottoia</i>

2015· article· en· W2128901068 on OpenAlexfundaboutno aff
Martin R. Smith, Thomas H. P. Harvey, Nicholas J. Butterfield

Bibliographic record

VenuePalaeontology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
FundersClare College, University of CambridgeNational Museum of Natural HistoryNatural Environment Research CouncilSight Research UKAmerican Chemical Society Petroleum Research FundParks Canada
KeywordsPaleontologyGeologyMacrofossilOil shaleLagerstätteRange (aeronautics)LithologyStructural basinSedimentary rockFacies

Abstract

fetched live from OpenAlex

Abstract The stem‐group priapulid Ottoia Walcott, 1911, is the most abundant worm in the mid‐Cambrian Burgess Shale, but has not been unambiguously demonstrated elsewhere. High‐resolution electron and optical microscopy of macroscopic Burgess Shale specimens reveals the detailed anatomy of its robust hooks, spines and pharyngeal teeth, establishing the presence of two species: Ottoia prolifica Walcott, 1911, and Ottoia tricuspida sp. nov. Direct comparison of these sclerotized elements with a suite of shale‐hosted mid‐to‐late Cambrian microfossils extends the range of ottoiid priapulids throughout the middle to upper Cambrian strata of the Western Canada Sedimentary Basin. Ottoiid priapulids represented an important component of Cambrian ecosystems: they occur in a range of lithologies and thrived in shallow water as well as in the deep‐water setting of the Burgess Shale. A wider survey of Burgess Shale macrofossils reveals specific characters that diagnose priapulid sclerites more generally, establishing the affinity of a wide range of Small Carbonaceous Fossils and demonstrating the prominent role of priapulids in Cambrian seas.

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 score0.113
Threshold uncertainty score0.224

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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

Citations77
Published2015
Admission routes2
Has abstractyes

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