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Record W4311452550 · doi:10.1029/2022gl100747

A Large New Crater Exposes the Limits of Water Ice on Mars

2022· article· en· W4311452550 on OpenAlexaff
C. M. Dundas, M. T. Mellon, L. Posiolova, Katarina Miljković, G. S. Collins, L. L. Tornabene, Vidhya Ganesh Rangarajan, M. P. Golombek, N. H. Warner, I. J. Daubar, Shane Byrne, A. S. McEwen, K. D. Seelos, D. Viola, A. M. Bramson, Gunnar Speth

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern University
FundersScience and Technology Facilities CouncilNuclear Safety and Security CommissionNational Aeronautics and Space Administration
KeywordsImpact craterMartianMars Exploration ProgramGeologyWater iceAstrobiologyLatitudeAtmosphere of MarsPlanetCryosphereClimatologyAtmospheric sciencesSea iceGeodesy

Abstract

fetched live from OpenAlex

Abstract Water ice in the Martian mid‐latitudes has advanced and retreated in response to variations in the planet's orbit, obliquity, and climate. A 150 m‐diameter new impact crater near 35°N provides the lowest‐latitude impact exposure of subsurface ice on Mars. This is the largest known ice‐exposing crater and provides key constraints on Martian climate history. This crater indicates a regional, relatively pure ice deposit that is unstable and has nearly vanished. In the past, this deposit may have been tens of meters thick and extended equatorward of 35°N. We infer that it is overlain by pore ice emplaced during temporary stable intervals, due to recent climate variability. The marginal survival of ice here suggests that it is near the edge of shallow ice that regularly exchanges with the atmosphere.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.056
GPT teacher head0.305
Teacher spread0.249 · 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 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

Citations49
Published2022
Admission routes1
Has abstractyes

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