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Record W2175430093 · doi:10.5194/tc-10-1381-2016

Modeling Antarctic subglacial lake filling and drainage cycles

2016· article· en· W2175430093 on OpenAlexaff
Christine F. Dow, Mauro Werder, Sophie Nowicki, R. T. Walker

Bibliographic record

Venue˜The œcryosphere · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
FundersGoddard Space Flight CenterOak Ridge Associated UniversitiesNational Aeronautics and Space Administration
KeywordsGeologyDrainage basinDrainageHydrology (agriculture)Flux (metallurgy)GeomorphologyIce streamDrainage system (geomorphology)Lead (geology)OceanographyCryosphereSea iceGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract. The growth and drainage of active subglacial lakes in Antarctica has previously been inferred from analysis of ice surface altimetry data. We use a subglacial hydrology model applied to a synthetic Antarctic ice stream to examine internal controls on the filling and drainage of subglacial lakes. Our model outputs suggest that the highly constricted subglacial environment of our idealized ice stream, combined with relatively high rates of water flow funneled from a large catchment, can combine to create a system exhibiting slow-moving pressure waves. Over a period of years, the accumulation of water in the ice stream onset region results in a buildup of pressure creating temporary channels, which then evacuate the excess water. This increased flux of water beneath the ice stream drives lake growth. As the water body builds up, it steepens the hydraulic gradient out of the overdeepened lake basin and allows greater flux. Eventually this flux is large enough to melt channels that cause the lake to drain. Lake drainage also depends on the internal hydrological development in the wider system and therefore does not directly correspond to a particular water volume or depth. This creates a highly temporally and spatially variable system, which is of interest for assessing the importance of subglacial lakes in ice stream hydrology and dynamics.

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 score0.221
Threshold uncertainty score0.999

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)0.0020.000

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 head0.020
GPT teacher head0.210
Teacher spread0.191 · 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

Citations36
Published2016
Admission routes1
Has abstractyes

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