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Record W3206108663 · doi:10.3847/psj/ac19a5

Past, Present, and Future of Mars Polar Science: Outcomes and Outlook from the 7th International Conference on Mars Polar Science and Exploration

2021· article· en· W3206108663 on OpenAlexaff
P. Becerra, I. B. Smith, Shannon M. Hibbard, Chimira Andres, J. Bapst, A. M. Bramson, P. B. Buhler, Andrea Coronato, S. Diniega, Jeremy Emmett, Anna Grau Galofre, Clémence Herny, M. A. Kahre, J. P. Knightly, S. Nerozzi, A. C. Pascuzzo, Ganna Portyankina, Jorge Rabassa, L. K. Tamppari, T. N. Titus, J. L. Whitten, Z. Yoldi

Bibliographic record

VenueThe Planetary Science Journal · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern UniversityYork University
FundersConsejo Nacional de Investigaciones Científicas y TécnicasSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsMars Exploration ProgramAstrobiologyPolarExploration of MarsEnvironmental scienceEarth scienceGeologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

Abstract Mars Polar Science is a subfield of Mars science that encompasses all studies of the cryosphere of Mars and its interaction with the Martian environment. Every 4 yr, the community of scientists dedicated to this subfield meets to discuss new findings and debate open issues in the International Conference on Mars Polar Science and Exploration (ICMPSE). This paper summarizes the proceedings of the seventh ICMPSE and the progress made since the sixth edition. We highlight the most important advances and present the most salient open questions in the field today, as discussed and agreed upon by the participants of the conference. We also feature agreed-upon suggestions for future methods, measurements, instruments, and missions that would be essential to answering the main open questions presented. This work is thus an overview of the current status of Mars Polar Science and is intended to serve as a road map for the direction of the field during the next 4 yr and beyond, helping to shape its contribution within the larger context of planetary science and exploration.

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)0.018
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0110.005
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.003

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 head0.024
GPT teacher head0.251
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2021
Admission routes1
Has abstractyes

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