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Record W4223933290 · doi:10.1144/jgs2022-047

Mars as a time machine to Precambrian Earth

2022· article· en· W4223933290 on OpenAlexafffund
M. G. A. Lapôtre, J. L. Bishop, Alessandro Ielpi, Donald R. Lowe, K. L. Siebach, Norman H. Sleep, Sonia M. Tikoo-Schantz

Bibliographic record

VenueJournal of the Geological Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMars Exploration ProgramGeologyMartianAstrobiologyGeologic recordEarth sciencePrecambrianImpact craterVolcanoEarly EarthMartian surfacePlate tectonicsTectonicsSedimentary rockPlanetPaleontology

Abstract

fetched live from OpenAlex

As Mars transitioned from an early Earth-like state to the cold desert planet it is today, it preserved a near pristine record of surface environments in a world without plate tectonics and complex life. The records of Mars’ Earth-like surfaces have remained largely untouched for billions of years, allowing space exploration to provide critical insights about the early days of our own planet. Here, we first review what Mars has taught us about volcanic, tectonic and metamorphic processes in the absence of discrete plates, drawing comparisons with the terrestrial and venusian records. Then, we summarize advances in understanding its early surface environments, including impact cratering, hydrological, sedimentary and geochemical processes. Altogether, the martian record provides a picture of early environments that were similar to modern terrestrial ones in many respects, with sediment and geochemical cycling, hydrothermal systems capable of hosting life, but with the exception that topography, sediment and heat sources were provided by volcanoes and impact cratering rather than plate tectonics. Mars thus offers a lens through which one might catch a glimpse of Earth's infancy, provided exploration efforts continue to refine our understanding of the similarities between Earth and Mars as well as the specificities of each planet.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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.

Study designNot applicable
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

Citations14
Published2022
Admission routes2
Has abstractyes

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