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Conodont Biostratigraphy of the Middle Cambrian through Lowermost Ordovician in Hunan, South China

2004· article· en· W1971476217 on OpenAlexaboutno aff
John E. Repetski, Stig M. Bergström

Bibliographic record

VenueActa Geologica Sinica - English Edition · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsConodontBiostratigraphyOrdovicianPaleontologyGeologyChinaGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Since 1985, samples with a total weight of more than 14,000 kg, mainly from three key sections in western and northwestern Hunan, South China, have been processed for conodonts. In strata older than the late Late Cambrian paraconodonts have proved useful for stratigraphic subdivision and correlation. Thirteen conodont zones are proposed in the Middle Cambrian through lowermost Ordovician. The correlation between these zones and those of North China, western U. S.A., western Newfoundland, Canada, and Iran is discussed. In ascending order, these 13 zones are as follows: The Gapparodus bisulcatus‐Westergaardodina brevidens Zone, Shandongodus priscus‐Hunanognathus tricuspidatus Zone, Westergaardodina quadrata Zone, Westergaardodina matsushitai‐W. grandidens Zone, Westergaardodina lui‐W. ani Zone, Westergaardodina cf. calix‐Prooneotodus rotundatus Zone, Proconodontus tenuiserratus Zone, Proconodontus Zone, Eoconodontus Zone, Cordylodus proavus Zone, Cordylodus intermedius Zone, Cordylodus lindstromi Zone, and Cordylodus angulatus Zone (lower part). The Westergaardodina lui‐W. ani and Westergaardodina cf. calix‐Prooneotodus rotundatus Zones replace the Westergaardodina proligula and Westergaardodina cf. behrae‐Prooneotodus rotundatus Zones, respectively, in the lowermost Upper Cambrian. Two new species ( Westergaardodina lui and Westergaardodina ani ) and one conditionally identified species ( Westergaardodina cf. calix ) are described.

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 score0.102
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.211
Teacher spread0.189 · 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

Citations60
Published2004
Admission routes1
Has abstractyes

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