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Record W2789788694 · doi:10.3847/1538-4357/aab767

Habitability from Tidally Induced Tectonics

2018· article· en· W2789788694 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsHabitabilityTerrestrial planetOutgassingPlanetPlanetary habitabilityCircumstellar habitable zoneTectonicsDefrosting

Abstract

fetched live from OpenAlex

Abstract The stability of Earth’s climate on geological timescales is enabled by the carbon–silicate cycle that acts as a negative feedback mechanism stabilizing surface temperatures via the intake and outgassing of atmospheric carbon. On Earth, this thermostat is enabled by plate tectonics that sequesters outgassed CO2 back into the mantle via weathering and subduction at convergent margins. Here we propose a separate tectonic mechanism—vertical recycling—that can serve as the vehicle for CO2 outgassing and sequestration over long timescales. The mechanism requires continuous tidal heating, which makes it particularly relevant to planets in the habitable zone of M stars. Dynamical models of this vertical recycling scenario and stability analysis show that temperate climates stable over timescales of billions of years are realized for a variety of initial conditions, even as the M star dims over time. The magnitude of equilibrium surface temperatures depends on the interplay of sea weathering and outgassing, which in turn depends on planetary carbon content, so that planets with lower carbon budgets are favored for temperate conditions. The habitability of planets such as found in the Trappist-1 system may be rooted in tidally driven tectonics.

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)0.000
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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
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

Citations17
Published2018
Admission routes1
Has abstractyes

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