MétaCan
Menu
← Back to cohort
Record W3095859552 · doi:10.1029/2020gl090431

The Rheological Behavior of CO<sub>2</sub> Ice: Application to Glacial Flow on Mars

2020· article· en· W3095859552 on OpenAlexaff
Andrew Cross, D. L. Goldsby, Travis F. Hager, I. B. Smith

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
FundersWoods Hole Oceanographic InstitutionNational Aeronautics and Space Administration
KeywordsMars Exploration ProgramGeologyMartianGlacial periodCreepPolarRheologyFlow (mathematics)GeophysicsGeomorphologyAstrobiologyMechanicsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Vast quantities of solid CO2 reside in topographic basins of the south polar layered deposits (SPLD) on Mars and exhibit morphological features indicative of glacial flow. Previous experimental studies showed that CO2 ice is 1–2 orders of magnitude weaker than water ice under Martian polar conditions. Here we present data from deformation experiments on pure, fine‐grained CO2 ice, over a broader range of temperatures than previously explored (158–213 K). The experiments confirm previous observations of highly nonlinear power law creep at larger stresses, but also show a transition to a previously unseen linear‐viscous creep regime at lower stresses. We examine the viscosity of CO2 within the SPLD and predict that the CO2‐rich deposits are modestly stronger than previously thought. Nevertheless, CO2 ice flows much more readily than H2O ice, particularly on the steep flanks of SPLD topographic basins, allowing the CO2 to pond as observed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.037
GPT teacher head0.307
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research Letters→Same topicPlanetary Science and Exploration→French-language works237,207→