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Record W2766721899 · doi:10.3997/2214-4609.201702160

Structural Geology Interpreted from AEM Data - Folded Terrain at the Foothills of Rocky Mountains, British Columbia

2017· article· en· W2766721899 on OpenAlexaffabout
Flemming Jørgensen, A. Menghini, Giulio Vignoli, Andrea Viezzoli, Cristhian Salas, Mel Best, Stig A. Schack Pedersen

Bibliographic record

VenueProceedings · 2017
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsGeoscience BC
Fundersnot available
KeywordsGeologySynclineAnticlineThrust faultSedimentary rockStructural geologyThrustFault (geology)CretaceousFoothillsGeologic mapFold and thrust beltSeismologyRegional geologyFold (higher-order function)GeomorphologyPaleontologyTectonicsPetrologyForeland basin

Abstract

fetched live from OpenAlex

Summary This study presents an interpretation of newly collected AEM data from the Peace Region, British Columbia, Canada. Through careful data processing and interpretation we demonstrate the potential for AEM methods to map traditional structural geology such as folds and thrust structures. The study area covers about 1,960 km2, and based on a dense grid of flight lines, a conceptual structural geological model has been developed. The geology of the region generally comprises Cretaceous rocks which are gently folded and displaced by shallow westerly dipping thrust faults. Alternating clay content of the stratigraphic formations in the area makes them detectable by the AEM data. Our structural model presents a sedimentary regime affected by gentle deformation and thin-skinned thrust faulting. We are able to resolve several anticlines, synclines and thrust faults. The main thrust fault is east-dipping, thus counter to the regional Laramide orogenic trend and likely represents a backthrust from a subcutaneous structure (triangle zone). We suggest a décollement level to be situated in or just below the clay-rich Buckinghorse Formation.

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)0.001
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 score0.167
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0050.005
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 head0.023
GPT teacher head0.245
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 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
Published2017
Admission routes2
Has abstractyes

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