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Record W2590485070 · doi:10.1130/b31582.1

A Late Cretaceous polygonal fault system in central North America

2017· article· en· W2590485070 on OpenAlexaboutno aff
Andy St‐Onge

Bibliographic record

VenueGeological Society of America Bulletin · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersGeological Society of America
KeywordsCitationCretaceousGeologyIconDownloadGeological surveyLibrary sciencePaleontologyWorld Wide WebComputer science

Abstract

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Research Article| May 01, 2017 A Late Cretaceous polygonal fault system in central North America Andy St-Onge Andy St-Onge 1PFS Interpretations Ltd., 427 28 Avenue NW, Calgary, Alberta T2M 2K7, Canada Search for other works by this author on: GSW Google Scholar Author and Article Information Andy St-Onge 1PFS Interpretations Ltd., 427 28 Avenue NW, Calgary, Alberta T2M 2K7, Canada Publisher: Geological Society of America Received: 23 May 2016 Revision Received: 28 Oct 2016 Accepted: 04 Dec 2016 First Online: 06 Jul 2017 Online Issn: 1943-2674 Print Issn: 0016-7606 © 2017 Geological Society of America GSA Bulletin (2017) 129 (5-6): 582–593. https://doi.org/10.1130/B31582.1 Article history Received: 23 May 2016 Revision Received: 28 Oct 2016 Accepted: 04 Dec 2016 First Online: 06 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Andy St-Onge; A Late Cretaceous polygonal fault system in central North America. GSA Bulletin 2017;; 129 (5-6): 582–593. doi: https://doi.org/10.1130/B31582.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGSA Bulletin Search Advanced Search Abstract Polygonal fault systems (PFS) have been interpreted worldwide using seismic data imaging sedimentary strata. Normal faults initiate over a large area in fine-grained subaqueous strata soon after deposition. As they continue to grow laterally and vertically, their fault traces intersect to form polygons in plan view. These polygons are difficult to image without three-dimensional (3-D) seismic data. The faulting is initiated during sediment dewatering and mud particle consolidation that can be independent of external stresses. In the past 20 years, hundreds of basins worldwide have been interpreted to contain polygonal faults.This paper presents a PFS interpretation for fine-grained sediments deposited in the Late Cretaceous Western Interior Seaway of the Great Plains of North America. The faulted strata have been observed as a PFS at depths ranging from ∼2750 m subsurface to outcrop. Seismic dataset interpretations and borehole analyses corroborate previously published outcrop analyses and seismic interpretations. The larger observed faults are mesoscale in size, with throws up to 80 m, and strike lengths up to ∼1.5 km. Potentially encompassing over 2,000,000 km2, observational averages imply 107 or more mesoscale-size faults, with an order of magnitude greater number of smaller faults. At shallow depth and outcrop, the PFS model of extensive normal faulting could help to explain Late Cretaceous shale faulting attributed to other causes such as deeper sediment dissolution or glacial processes. In the subsurface, faulting and fracturing consistent with a PFS model can help to explain fault geometries observed in well control and 3-D seismic data. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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 score0.459
Threshold uncertainty score0.913

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.206
Teacher spread0.195 · 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".

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Citations6
Published2017
Admission routes1
Has abstractyes

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