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Record W3049197987 · doi:10.1029/2020je006575

Mars: Abundant Recurring Slope Lineae (RSL) Following the Planet‐Encircling Dust Event (PEDE) of 2018

2021· article· en· W3049197987 on OpenAlexaff
A. S. McEwen, E. I. Schaefer, C. M. Dundas, Sarah Sutton, L. K. Tamppari, M. Chojnacki

Bibliographic record

VenueJournal of Geophysical Research Planets · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern University
Fundersnot available
KeywordsMars Exploration ProgramDust stormGeologyLongitudeLatitudeAtmosphere of MarsOrbiterStormAstrobiologyMartianOceanographyAstronomyPhysicsGeodesy

Abstract

fetched live from OpenAlex

Abstract Recurring slope lineae (RSL) are dark linear markings on Mars that regrow annually and likely originate from the flow of either liquid water or granular material. Following the great dust storm (or planet‐encircling dust event, PEDE) of Mars year (MY) 34, Mars Reconnaissance Orbiter/High Resolution Imaging Science Experiment has seen many more candidate RSL than in typical Mars years. They have been imaged at more than 285 unique locations from August 2018 (when the atmosphere was clearing as the PEDE decayed) to August 2019, about half (157) of which are locations where RSL have not been documented previously. In MY34, 150 active RSL sites were identified in the southern middle latitudes (SML, ‐60° to ‐30°), whereas an average of 36 active sites were observed in each previous year (MY28–33). Post‐PEDE RSL are also present during southern summer over a wider range of latitude, slope aspect, and L s (areocentric longitude of the sun) than in prior years. These RSL sites usually show evidence for recent dust deposition: obscuration of relatively dark areas, an overall brighter and redder surface than in prior years, and dust devil tracks, which indicate dust lifting by several mechanisms. We speculate that dust‐lifting processes may initiate and sustain RSL activity. The RSL may form from flows of dust (perhaps clumped) and/or sand that is destabilized by dust movement or directly mobilized by dust devils. If this is the case, then the otherwise puzzling recurrence and year‐to‐year variability of RSL activity can be at least partly explained. The dust replenishment varies from year to year, which could explain interannual variations in RSL activity.

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 score0.307
Threshold uncertainty score0.370

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 communication0.0000.000
Open science0.0000.000
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 head0.056
GPT teacher head0.344
Teacher spread0.287 · 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

Citations32
Published2021
Admission routes1
Has abstractyes

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