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Record W3005409946 · doi:10.1080/08912963.2020.1719084

A theropod and sauropod track assemblage from the Lower Jurassic of Guizhou, China

2020· article· en· W3005409946 on OpenAlexaff
Lida Xing, Martin G. Lockley, Hendrik Klein, Rong Zeng, Guangzhao Peng, Yong Ye, Baoqiao Hao, W. Scott Persons

Bibliographic record

VenueHistorical Biology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsUniversity of Alberta
FundersState Key Laboratory of Palaeobiology and StratigraphyFundamental Research Funds for the Central UniversitiesChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsTetrapod (structure)PaleontologyFaunaGeologyChinaAssemblage (archaeology)GeographyArchaeologyBiologyEcology

Abstract

fetched live from OpenAlex

The newly discovered Maoshajing tracksite in the Lower Jurassic Longtoushan Group of Guizhou Province, China is dominated by well-preserved medium-sized theropod tracks of the Grallator-Eubrontes plexus type, and associated with a few sauropod tracks. This saurischian dominated ichnofauna is typical of the Lower Jurassic biochron of China and elsewhere. It is also consistent with the sparse body fossil record, making it a type 2a deposit in which tracks are more abundant, and therefore also more important in providing a useful census of the tetrapod fauna. It is argued that small tracksite surfaces are more useful in ‘capturing’ (registering) evidence of small and potentially more active theropod movements than the activity of larger saurischians (sauropodomorphs) which may have been less abundant and less active in areas of any given size.

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 score0.228
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.206
Teacher spread0.186 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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