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Record W4315568120 · doi:10.1029/2022je007443

Assessing Controls on the Incomplete Draining of Martian Open‐Basin Lakes

2023· article· en· W4315568120 on OpenAlexaff
T. A. Goudge, C. I. Fassett, Marianne Coholich, Emily Bamber

Bibliographic record

VenueJournal of Geophysical Research Planets · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsCanadian Institute for Advanced Research
FundersNuclear Safety and Security CommissionNational Aeronautics and Space Administration
KeywordsGeologyMars Exploration ProgramMartianStructural basinFluvialImpact craterGeomorphologyLandformHydrology (agriculture)Geotechnical engineeringAstrobiology

Abstract

fetched live from OpenAlex

Abstract Over 250 hydrologically open paleolakes, which filled with water before catastrophically breaching, have been identified on Mars. These open‐basin lakes are recognized by the topographic geometry of a closed contour below the elevation of the outlet, indicating that the lake was incompletely drained by the breach flood. Here, we explore factors that controlled how completely a given open‐basin lake on Mars drained using (a) observations of 24 open‐basin lakes on Mars and (b) numerical modeling experiments of lake breach flooding. Observational results suggest that the key parameters for promoting more complete draining in open‐basin lakes on Mars were steeper regional slopes and taller crater rims. From a suite of 303 numerical experiments, we find that more complete draining is accomplished with larger basins, steeper regional slopes, basins with steeper walls, taller crater rims, and a more erodible substrate (parameterized by grain size in our model). Outliers in the observational results suggest that complete draining was inhibited by the presence of another lake immediately downstream of the breach as well as a less erodible substrate relative to other basins. We observe no correlation between open‐basin lake area and drained fraction on Mars, contrary to the strong trend in our numerical experiments. We hypothesize that this is the result of increasing resistance to erosion with depth in the Martian crust, which is not incorporated into our model. Our results provide new insights into controls on the fluvial integration of the early Mars landscape as well as the spatially variable erodibility of the shallow Martian crust.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.183
GPT teacher head0.409
Teacher spread0.226 · 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.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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