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Record W2135456474 · doi:10.1002/2013gl058877

Surface of Ligeia Mare, Titan, from Cassini altimeter and radiometer analysis

2014· article· en· W2135456474 on OpenAlexaboutno aff
H. A. Zebker, Alex Hayes, Alice Le Gall, R. D. Lorenz, Lauren Wye

Bibliographic record

VenueGeophysical Research Letters · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsTitan (rocket family)RadiometerGeologyAltimeterNadirRadarRadar altimeterSpecular reflectionTerrainAstrobiologyRemote sensingAtmospheric sciencesSatelliteOpticsPhysicsAstronomy

Abstract

fetched live from OpenAlex

Abstract Cassini radar observations of the surface of Ligeia Mare collected during the 23 May 2013 (T91) Cassini flyby show that it is extremely smooth, likely to be mostly methane in composition, and exhibits no surface wave activity. The radar parameters were tuned for nadir‐looking geometry of liquid surfaces, using experience from Cassini's only comparable observation, of Ontario Lacus on 21 December 2008 (T49), and also include coincident radiometric observations. Radar echoes from both passes show very strong specular radar reflections and limit surface height variations to 1 mm rms. The surface physical temperature at 80°N is 92 +/− 0.5 K if the sea is liquid hydrocarbon and the land is solid hydrocarbon, essentially the same as Cassini CIRS measurements. Furthermore, radiometry measurements over the surrounding terrain suggest dielectric constants from 2.2 to 2.4, arguing against significant surface water ice unless it is extremely porous.

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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.293
Teacher spread0.268 · 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

Citations55
Published2014
Admission routes1
Has abstractyes

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