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Record W4311507207 · doi:10.1029/2022gl101097

Paleolake Inlet Valley Formation: Factors Controlling Which Craters Breached on Early Mars

2022· article· en· W4311507207 on OpenAlexaff
Emily Bamber, T. A. Goudge, C. I. Fassett, G. R. Osinski, Gaia Stucky de Quay

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern UniversityCanadian Institute for Advanced Research
FundersNuclear Safety and Security CommissionNational Aeronautics and Space Administration
KeywordsImpact craterMars Exploration ProgramGeologyMartianInletFluvialNoachianGeomorphologyStructural basinEarth scienceHydrology (agriculture)AstrobiologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The ancient surface of Mars is dominated by degraded impact craters with reduced or eliminated rim relief. Some degraded craters have an inlet valley, while many remain fluvially isolated. Despite controlling Martian fluvial connectivity, few constraints exist on why some—but not all—degraded craters possess inlets. We compared a suite of properties around degraded Martian craters with and without inlets to ascertain what topographic and hydrologic factors influenced inlet formation. Slope and surface roughness are similar, but topographic inset within the catchment, drainage density, and potential contributing areas diverge for breached and non‐breached craters. We suggest that the importance of basin hydrology‐related factors over topographic factors is the result of the former less frequently surpassing inlet incision thresholds than the latter. We conclude that greater topographic inset (i.e., craters deeper within regional depressions) promoted higher discharge, and that inlet valley formation was ultimately controlled by Mars' crater‐dominated topography.

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)0.001
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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.044
GPT teacher head0.282
Teacher spread0.238 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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