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Record W2325160388 · doi:10.1139/cjes-2012-0146

Summary of fossil vertebrate taxa named by Richard C. Fox, with an annotated list of taxa named between 1962 and 2012 and new photographs for non-mammalian therapsid and mammalian holotypes erected between 1968 and 1994

2012· article· en· W2325160388 on OpenAlexafffundvenueabout
Craig S. Scott, James D. Gardner

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsRoyal Tyrrell Museum
FundersUniversity of Alberta
KeywordsVertebrate paleontologyVertebrateCretaceousTaxonPaleontologyMammalGeologyFaunaArchaeologyGeographyBiologyEcology

Abstract

fetched live from OpenAlex

Beginning in 1962 and extending to the present, Richard C. Fox and colleagues have named 87 species of fossil vertebrates (1 fish, 4 amphibians, 2 choristoderes, 12 lizards, 1 crocodile, 1 dinosaur, 2 “pelycosaurs”, 2 non-mammalian therapsids, and 62 mammals) and numerous new supraspecific taxa. Virtually all of these species continue to be accepted, although the higher-level assignments of several have been altered. The vast majority of the named species were founded on specimens, collected during the mid-1960s to early 2000s by field parties under Fox’s direction, from the Late Cretaceous (late Santonian to late Maastrichtian) and Paleocene of Alberta and Saskatchewan, Canada, and that are housed at the University of Alberta Laboratory for Vertebrate Paleontology. Here we present (i) an annotated list of all fossil vertebrate species named by Richard Fox between 1962 and 2012, (ii) updated information on the stratigraphic nomenclature and age estimates for the eight localities in Alberta that yielded holotypes for all the Cretaceous mammal species named by Richard Fox from that province, and (iii) new photographs for the holotypes of the one non-mammalian therapsid and 43 Late Cretaceous and Paleocene mammal species named by Richard Fox before 1995.

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)0.001
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 score0.393
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.238
Teacher spread0.210 · 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

Citations3
Published2012
Admission routes4
Has abstractyes

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