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Record W2124154663 · doi:10.1098/rsta.2006.1877

: the driver of giant planet atmospheres

2006· article· en· W2124154663 on OpenAlexaff
S. Miller, Tom Stallard, C. Smith, George Millward, Henrik Melin, Makenzie Lystrup, A. D. Aylward

Bibliographic record

VenuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsSaturnUranusPlanetPhysicsJupiter (rocket family)Atmosphere (unit)AstrobiologyGas giantSolar SystemOuter planetsAstronomyExoplanetMeteorologySpace exploration

Abstract

fetched live from OpenAlex

We present a review of recent developments in the use of H3+ molecular ion as a probe of physics and chemistry of the upper atmospheres of giant planets. This ion is shown to be a good tracer of energy inputs into Jupiter (J), Saturn (S) and Uranus (U). It also acts as a 'thermostat', offsetting increases in the energy inputs owing to particle precipitation via cooling to space (J and U). Computer models have established that H3+ is also the main contributor to ionospheric conductivity. The coupling of electric and magnetic fields in the auroral polar regions leads to ion winds, which, in turn, drive neutral circulation systems (J and S). These latter two effects, dependent on H3+, also result in very large heating terms, approximately 5 x 10(12) W for Saturn and greater than 10(14) W for Jupiter, planet-wide; these terms compare with approximately 2.5 x 10(11) W of solar extreme UV absorbed at Saturn and 10(12) W at Jupiter. Thus, H3+ is shown to play a major role in explaining why the temperatures of the giant planets are much greater (by hundreds of kelvin) at the top of the atmosphere than solar inputs alone can account for.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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
Published2006
Admission routes1
Has abstractyes

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