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Record W2979334553 · doi:10.1130/2018.2541(28)

Latest Cretaceous–early Eocene Pacific-Arctic?-Atlantic connection: Co-evolution of strike-slip fault systems, oroclines, and transverse fold-and-thrust belts in the northwestern North American Cordillera

2019· book-chapter· en· W2979334553 on OpenAlexaffabout
Donald C. Murphy

Bibliographic record

VenueGeological Society of America eBooks · 2019
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsYukon University
Fundersnot available
KeywordsGeologyPaleontologyTransform faultPlate tectonicsCretaceousThrust faultPaleogeneSeafloor spreadingArcticNorth American PlateRiftSeismologyFault (geology)OceanographyTectonics

Abstract

fetched live from OpenAlex

ABSTRACT Comprehensive understanding of the pre-Paleogene kinematic evolution of the North American Cordillera in the context of evolving global plate interactions must begin with an understanding of the complex Late Cretaceous–early Eocene structural geometry and evolution of the northwestern Cordillera of Alaska, United States, and Yukon, Canada. Here, I present a kinematic model of the region that shows how regional strike-slip fault systems, including plate-boundary transform faults, interacted with each other, and with north-striking oroclinal folds and fold-and-thrust belts, which formed progressively during coeval shortening between Eurasia and North America. These Late Cretaceous–early Eocene interactions are manifestations of the plate reorganizations in the Pacific and Atlantic-Arctic regions that took place at that time, and that led to rifting and seafloor spreading within the globe-encircling Eurasian–North American plate and to the formation of transform-dominant North American–Pacific (sensu lato) and possibly North American–Arctic plate boundaries.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.002

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 head0.014
GPT teacher head0.192
Teacher spread0.178 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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