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Record W233310673

PLANETARY ANALOG STUDIES AND SIMULATIONS: MATERIALS, TERRAINS, MORPHOLOGIES, PROCESSES: CONCISE ATLAS IN THE SOLAR SYSTEM (9) EÖTVÖS UNIVERSITY, HUNGARY. Gy. Hudoba 1 , S.

2006· article· en· W233310673 on OpenAlexaboutno aff
Gy. Hudoba, S. Hegyi, Henrik Hargitai, A. Gucsik, Sándor Józsa, Ákos Keresztúri, A. Sik, Gy. Szakmány, T. Földi, Pé ter Gadányi, Sz. Bérczi

Bibliographic record

Venue37th Annual Lunar and Planetary Science Conference · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsImpact craterMars Exploration ProgramAstrobiologyGeologyHesperianMartianTerrainSolar SystemEarth scienceLavaNoachianVolcanoGeographyPaleontologyCartography
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Transfer of ideas from terrestrial works to planetary ones can be intensified by analog methods. Among others, analog studies of comparative planetary geology play a key role in planetary science education. The whole system of terrestrial geology knowledge can be transformed to other planetary conditions if we compare and fit them to the conditions on the other planet. Analog site field works for Apollo astronauts: Various analog planetary geology studies were organized first for astronauts preparing to the lunar landing in the Apollo Era. American desert and mountainous regions were visited by them in the Grand Canyon and Arizona (Meteor crater) and other sites. Recently the Mars is the main object for manned and robotic research. Mars analog terrains can be found in several places on the Earth. Haughton crater in Devon Island, Canada and Antarctic terrains are cold desert places, where impact processes (Haughton crater) and extremely cold conditions (both places) are present. For analog sites with Martian volcanism together with ice, glaciers, ice-lava interactions the islands of Iceland and Svalbard seem excellent places.

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)0.001
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 score0.182
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venue37th Annual Lunar and Planetary Science ConferenceSame topicPlanetary Science and ExplorationFrench-language works237,207