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Record W2307346385

Recommended Maximum Temperature for Mars Returned Samples

2016· article· en· W2307346385 on OpenAlexaff
D. W. Beaty, H. Y. McSween, Andrew D. Czaja, Y. S. Goreva, Elisabeth M. Hausrath, C. D. K. Herd, M. Humayun, F. M. McCubbin, S. M. McLennan, L. E. Hays

Bibliographic record

VenueLPI · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMars Exploration ProgramMartianEnvironmental scienceMaterials scienceGeologyMineralogyAstrobiologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

The Returned Sample Science Board (RSSB) was established in 2015 by NASA to provide expertise from the planetary sample community to the Mars 2020 Project. The RSSB's first task was to address the effect of heating during acquisition and storage of samples on scientific investigations that could be expected to be conducted if the samples are returned to Earth. Sample heating may cause changes that could ad-versely affect scientific investigations. Previous studies of temperature requirements for returned mar-tian samples fall within a wide range (-73 to 50 degrees Centigrade) and, for mission concepts that have a life detection component, the recommended threshold was less than or equal to -20 degrees Centigrade. The RSSB was asked by the Mars 2020 project to determine whether or not a temperature requirement was needed within the range of 30 to 70 degrees Centigrade. There are eight expected temperature regimes to which the samples could be exposed, from the moment that they are drilled until they are placed into a temperature-controlled environment on Earth. Two of those - heating during sample acquisition (drilling) and heating while cached on the Martian surface - potentially subject samples to the highest temperatures. The RSSB focused on the upper temperature limit that Mars samples should be allowed to reach. We considered 11 scientific investigations where thermal excursions may have an adverse effect on the science outcome. Those are: (T-1) organic geochemistry, (T-2) stable isotope geochemistry, (T-3) prevention of mineral hydration/dehydration and phase transformation, (T-4) retention of water, (T-5) characterization of amorphous materials, (T-6) putative Martian organisms, (T-7) oxidation/reduction reactions, (T-8) (sup 4) He thermochronometry, (T-9) radiometric dating using fission, cosmic-ray or solar-flare tracks, (T-10) analyses of trapped gasses, and (T-11) magnetic studies.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.013

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 head0.238
Teacher spread0.214 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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