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Record W4387955516 · doi:10.2110/jsr.2022.017

Subglacial tills: a process model based on microsedimentological clues

2023· article· en· W4387955516 on OpenAlexafffundabout
John Menzies, R C Paulen, Jürgen M. Reitner, Cunhai Gao, Tyler Hodder, Martin Ross

Bibliographic record

VenueJournal of Sedimentary Research · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsManitoba HydroUniversity of WaterlooGeological Survey of CanadaBrock University
FundersNatural Resources CanadaBrock UniversityNational Energy Research Scientific Computing Center
KeywordsGeologyGeomorphologyGlacial periodGlacierBedformSedimentDeposition (geology)Sedimentary rockSediment transportEarth scienceGeochemistry

Abstract

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Abstract Subglacial sediments are subject to erosion, transport, and deposition in active, ephemeral, and spatially localized glacial environments. It is critical to determine how these mobilized sediments become immobilized in a time-transgressive process and can be frequently remobilized and reimmobilized. Microscopic sedimentary structural signatures provide invaluable information on subglacial processes and contribute to understanding till formation. Data were obtained from a series of field sites in Canada and Austria investigating the microsedimentological aspects of both alpine and continental glaciation tills to construct a conceptual model of subglacial deformation. Microstructures in these tills indicate rheological behaviors that can be summarized into a potential model for soft deforming subglacial sediments. Most microstructures noted in these subglacial till examples highlight the development of subglacial interface kinematics providing clues to till deposition mechanics, subglacial bedform development, and the processes involved in till provenance distributions. A conceptual process model of subglacial interface conditions in soft mobile sediments is developed that uses microsedimentological evidence and highlights how an active ice mass integrates with ongoing substrate deformation. In the model, interaction occurs between the ice and its sediment bed with internal sediment microstructures evolving where multiple transient shear deformation processes cause localized deformation linked to pervasive and nonpervasive sediment deformation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.137
GPT teacher head0.384
Teacher spread0.248 · 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.

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

Citations5
Published2023
Admission routes3
Has abstractyes

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