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Record W3102114034 · doi:10.1038/s41467-020-19336-1

Tesserae on Venus may preserve evidence of fluvial erosion

2020· article· en· W3102114034 on OpenAlexafffund
S. Khawja, Richard E. Ernst, C. Samson, P. K. Byrne, Richard Ghail, L. M. MacLellan

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaMegagrants
KeywordsFluvialVenusGeologyErosionVolcanismVolcanoEarth scienceAeolian processesTectonicsLavaClimate changeGeomorphologyPaleontologyAstrobiologyOceanographyStructural basin

Abstract

fetched live from OpenAlex

Fluvial erosion is usually assumed to be absent on Venus, precluded by a high surface temperature of ~450 °C and supported by extensive uneroded volcanic flows. However, recent global circulation models suggest the possibility of Earth-like climatic conditions on Venus for much of its earlier history, prior to catastrophic runaway greenhouse warming. We observe that the stratigraphically oldest, geologically most complex units, tesserae, exhibit valley patterns morphologically similar to the patterns resulting from fluvial erosion on Earth. Given poor topographic resolution, we use an indirect technique to recognize valleys, based on the pattern of lava flooding of tesserae margins by adjacent plains volcanism. These observed valley patterns are attributed to primary geology, tectonic deformation, followed by fluvial erosion (and lesser wind erosion). This proposed fluvial erosion in tesserae provides support for climate models for a cool, wet climate on early Venus and could be an attractive research theme for future Venus missions.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.200

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.322
Teacher spread0.252 · 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

Citations39
Published2020
Admission routes2
Has abstractyes

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