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Record W2329977100 · doi:10.3189/2014jog14j027

A test of common assumptions used to infer subglacial water flow through overdeepenings

2014· article· en· W2329977100 on OpenAlexafffund
Christine F. Dow, Jeffrey L. Kavanaugh, J. W. Sanders, Kurt M. Cuffey

Bibliographic record

VenueJournal of Glaciology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
FundersNatural Environment Research CouncilUniversity of AlbertaBritish Columbia Ministry of Agriculture and LandsNational Science Foundation
KeywordsGeologyBoreholeGlacierHydraulic conductivityOverburdenGeomorphologyCirqueStructural basinHydrology (agriculture)Geotechnical engineeringSoil science

Abstract

fetched live from OpenAlex

Abstract Borehole instrument records from a cirque glacier with an overdeepened bed are examined to assess the validity of widely held glacial hydrological assumptions. At this glacier, hydraulic-potential calculations suggest water below overburden pressure will flow into the overdeepening, where the steepness of the riegel causes water to pool in the basin and increase in pressure. Our subglacial water pressure data also show high consistent pressures in the overdeepening and the presence of an active, variable-pressure drainage system towards the margin of the cirque. Therefore, we find that although uniform hydraulic-potential calculations are not directly applicable, they can still be useful for interpretation of the subglacial hydrological system. We also examine supercooling assumptions under different pressure and temperature regimes for water flowing over a riegel, driven using our borehole records of subglacial water temperatures that are consistently above the pressure-melting point during the late melt season. Our results show that even a slight increase in basal temperatures relative to the local pressure-melting point is sufficient to prevent a reduction in basal hydraulic conductivity as a result of supercooling freeze-on.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
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 studies0.0000.000
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 head0.028
GPT teacher head0.256
Teacher spread0.228 · 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

Citations9
Published2014
Admission routes2
Has abstractyes

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