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Record W1562841537 · doi:10.1002/asna.201211776

Clouds in brown dwarfs and giant planets

2013· article· en· W1562841537 on OpenAlex
Stanimir Metchev, Dániel Apai, Jacqueline Radigan, Étienne Artigau, A. Heinze, Ch. Helling, D. Homeier, S. P. Littlefair, Caroline Morley, Andrew Skemer, C. R. Stark

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAstronomische Nachrichten · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de MontréalUniversity of Toronto
FundersScience and Technology Facilities Council
KeywordsBrown dwarfPlanetPhysicsOpacityAstrophysicsAstronomyAstrobiology

Abstract

fetched live from OpenAlex

Abstract A growing body of observational and theoretical evidence points toward the importance of clouds in the atmospheres of ultra‐cool brown dwarfs and giant planets. Empirically, the presence of clouds is inferred from the red, likely dusty atmospheres of young substellar objects, and from detections of periodic variability in a fraction of brown dwarfs – as expected from rotation and a patchy cloud cover. Theoretical models have progressed alongside by including ever more comprehensive atomic and molecular opacity tables, incorporating the treatment of non‐equilibrium chemistry and clouds through vertical mixing and grain size/sedimentation parameters, and employing 3‐D hydrodynamical simulations. In this proceeding we summarize the key issues raised during the first gathering of observers and theorists to discuss clouds and atmospheric circulation in non‐irradiated ultra‐cool dwarfs and giant planets. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.008
GPT teacher head0.204
Teacher spread0.195 · 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