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Record W1993815857 · doi:10.1098/rspa.2014.0907

Modelling water flow under glaciers and ice sheets

2015· review· en· W1993815857 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2015
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGlacierGeologyChannelizedDrainageIce sheetIce streamFlow (mathematics)Drainage system (geomorphology)GeomorphologyEarth scienceCryosphereClimatologyComputer scienceSea iceMechanics

Abstract

fetched live from OpenAlex

Recent observations of dynamic water systems beneath the Greenland and Antarctic ice sheets have sparked renewed interest in modelling subglacial drainage. The foundations of today's models were laid decades ago, inspired by measurements from mountain glaciers, discovery of the modern ice streams and the study of landscapes evacuated by former ice sheets. Models have progressed from strict adherence to the principles of groundwater flow, to the incorporation of flow 'elements' specific to the subglacial environment, to sophisticated two-dimensional representations of interacting distributed and channelized drainage. Although presently in a state of rapid development, subglacial drainage models, when coupled to models of ice flow, are now able to reproduce many of the canonical phenomena that characterize this coupled system. Model calibration remains generally out of reach, whereas widespread application of these models to large problems and real geometries awaits the next level of development.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.379
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.040
GPT teacher head0.236
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