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Record W4378222196 · doi:10.1134/s0869593823030048

Late Albian–Early Turonian Grebenka Flora of the North Pacific: Systematic Composition, Age, Distribution

2023· article· en· W4378222196 on OpenAlexaboutno aff
A. B. Herman, S. V. Shczepetov

Bibliographic record

VenueStratigraphy and Geological Correlation · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentologyHistorical geologyStructural geologyGeologyFlora (microbiology)PaleontologyDistribution (mathematics)Composition (language)GeographyPhysical geographyOceanographyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Beginning from the mid-Cretaceous and in the Late Cretaceous, the landscape features of the North Pacific make it possible to divide this region into a number of territories called subregions. The earliest Cenophytic (with a significant number and diversity of angiosperms) late Albian–early Turonian Grebenka flora and its analogs are known only in three subregions of the North Pacific: Anadyr–Koryak, Northern Alaska, and Yukon–Koyukuk. In the middle of the Cretaceous, these subregions represented coastal plains and lowlands periodically flooded by the sea. Cenophytic floras populated the area of terrestrial volcanism of the Okhotsk–Chukotka subregion and the Asian continental interiors of the Verkhoyansk–Chukotka subregion later, in the Turonian–Coniacian. However, Mesophytic vegetation with the predominance of Early Cretaceous ferns and gymnosperms continued to exist there at least until the Coniacian. Consequently, the invasion of evolutionarily new Cenophytic vegetation into the continental interiors of Northeast Asia was gradual and extended over time. This should be taken into account when studying the Cretaceous nonmarine phytostratigraphy of the North Pacific region.

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 score0.007
Threshold uncertainty score0.372

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 studies0.0000.000
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 head0.014
GPT teacher head0.200
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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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