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A case for formalizing subseries (subepochs) of the Cenozoic Era<sup>(a)</sup>

2017· article· en· W2598793577 on OpenAlexafffund
Martin J. Head, Marie-Pierre Aubry, Mike Walker, Kenneth G. Miller, Brian R. Pratt

Bibliographic record

VenueEpisodes · 2017
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of SaskatchewanBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCenozoicGeologyPaleontology

Abstract

fetched live from OpenAlex

Subseries/subepochs (e.g., Lower/Early Eocene, Upper/ Late Pleistocene) have yet to be formally defined despite their wide use in the Cenozoic literature. This has led to concerns about the stability of their definition and uncertainty over their status that has led to inconsistencies in capitalization. To address these issues, we propose for the Cenozoic that subseries/subepochs be defined formally by reference to Global Boundary Stratotype Sections and Points and ratified in the same way as for other formal chronostratigraphic units. Formalization of subseries/subepochs for the Cenozoic will respect their deep historical roots, recognise their chronostratigraphic nature, stabilize their definition, ensure consistency in application, embrace their de-facto use as formal terms within the Paleogene, Neogene and especially Quaternary communities, and resolve the question of capitalization: an upper-case initial letter without exception.

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)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.020
Scholarly communication0.0050.015
Open science0.0030.006
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0040.002

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 head0.033
GPT teacher head0.256
Teacher spread0.223 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations35
Published2017
Admission routes2
Has abstractyes

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