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Record W7005637738

Restoration and Balancing of a Cross Section of the Mt. Crandell Duplex, Waterton National Park, Canada

2023· article· en· W7005637738 on OpenAlexaboutno aff

Bibliographic record

VenueScholarly and Creative Works from DePauw University (DePauw University) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)Deformation (meteorology)Feature (linguistics)Filter (signal processing)Context (archaeology)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

Cross-section balancing provides a useful tool for checking the potential viability of structural interpretations through complexly deformed terranes. Balanced cross sections contain structures that are similar to those observed in outcrop or on seismic profiles in the area, that can be restored to a realistic pre-deformational configuration of faults and undeformed strata where areas are preserved between the deformed and restored states, and whose development from the undeformed state can be described in a kinematically reasonable sequence. Quick-look inspection of cross sections greatly facilitates the balancing process by comparing corresponding hanging wall and footwall features (particularly focusing on ramps and flats) to identify areas in a cross section that may contain balancing issues. The well-known Boyer and Elliott (1982) cross section through the Mt. Crandell duplex in Waterton National Park in Alberta, Canada and its accompanying restoration have long served as a classic example of a balanced cross section. We carefully examined the section and its restoration using quick-look techniques, and noted several structures that had substantially changed their shape between the deformed and restored states, had ramp-flat mismatches between the hanging wall and footwall, and/or had significant area changes between the deformed and restored states. Using cross-section restoration software, we not only quantified differences between their deformed-state and restored-state cross sections, but we also rigorously restored their original section. Specifically, we identified differences where restored layer areas ranged from 18.3% to 186% of the areas of their deformed counterparts, with some layers missing or incomplete. In addition, the computerized restoration revealed multiple issues with ramp-flat geometries that produced substantial gaps and overlaps not reflected in the original restoration. Based on careful examination of these problematic areas, we are currently working on refining the Boyer and Elliott (1982) deformed-state cross section to address these issues.

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 score0.375
Threshold uncertainty score0.712

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.195
Teacher spread0.182 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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