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Record W4388717007 · doi:10.5194/tc-17-4817-2023

The evolution of isolated cavities and hydraulic connection at the glacier bed – Part 2: A dynamic viscoelastic model

2023· article· en· W4388717007 on OpenAlexafffund
Christian Schoof

Bibliographic record

Venue˜The œcryosphere · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsGeologyViscoelasticityGlacierCavitationScale (ratio)MechanicsFlow (mathematics)Representation (politics)Work (physics)Geotechnical engineeringGeomorphologyPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract. Many large-scale subglacial drainage models implicitly or explicitly assume that the distributed part of the drainage system consists of subglacial cavities. Few of these models, however, consider the possibility of hydraulic disconnection, where cavities exist but are not numerous or large enough to be pervasively connected with one another so that water can flow. Here I use a process-scale model for subglacial cavities to explore their evolution, focusing on the dynamics of connections that are made between cavities. The model uses a viscoelastic representation of ice and computes the pressure gradients that are necessary to move water around basal cavities as they grow or shrink. The latter model component sets the work here apart from previous studies of subglacial cavities and permits the model to represent the behaviour of isolated cavities as well as of uncavitated parts of the bed at low normal stress. I show that connections between cavities are made dynamically when the cavitation ratio (the fraction of the bed occupied by cavities) reaches a critical value due to decreases in effective pressure. I also show that existing simple models for cavitation ratio and for water sheet thickness (defined as mean water depth) fail to even qualitatively capture the behaviour predicted by the present model.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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 designSimulation or modeling
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 routes2
Has abstractyes

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