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Record W4220773326 · doi:10.5194/egusphere-egu22-4357

Heat-death by volcano - how Venus went rogue?

2022· preprint· en· W4220773326 on OpenAlexaff
M. J. Way, Richard E. Ernst, Jeffrey Scargle

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsCarleton University
Fundersnot available
KeywordsLife spanVenusSpan (engineering)MeteorologyEnvironmental scienceAstrobiologyPhysicsBiologyEngineering

Abstract

fetched live from OpenAlex

The idea of a habitable Venus epoch has gained traction in recent years via 1-D and 3-D General Circulation Modeling (GCM) efforts [1,2,3]. Although recent work has supported an alternative permanent hot and dry scenario [4]. However, the habitable scenario presents us with a conundrum - how does a terrestrial planet transform from temperate to hot-house? For decades it was proposed that the gradual brightening of the sun was the probable cause [5]. Yet 4 billion years ago Venus was receiving nearly 1.4 times the insolation that Earth receives today, and many studies have put Earth at the inner boundary of the habitable zone today [6]. The newer 3-D GCM efforts have demonstrated that if Venus had an early habitable period, that the cloud-albedo feedback responsible for maintaining temperate surface conditions [7] could still be in operation today. From this perspective increasing insolation through time cannot be an answer to the transition from habitable to hot-house. We propose that the 'Great Climate Transition' (GCT) was trigged by simultaneous large igneous provinces (LIPs) akin to those like the Siberian Traps responsible for the End Permian [8]. We have taken the most up to date LIP database for Earth [9] and characterized their distribution through time as random or nearly random. Next we initiate a large suite of Monte Carlo simulations based on this record and generate the likelihood for simultaneous, or environmentally overlapping events in this hypothetical setup. We find the probability of such events to be quite high, a probable cause for Venus' GCT, and a possible harbinger of things to come for Earth. [1] Grinspoon, D.H. & Bullock, M.A. (2007) AGU https://doi.org/10.1029/176GM12 [2] Way, M. J. et al. (2016) GRL 43, 8376–8383 [3] Way, M. J. and Del Genio, A D. (2020) JGR Planets 125, e2019JE006276 [4] Turbet et al. (2021) Nature,598,276 https://doi.org/10.1038/s41586-021-03873-w [5] Kasting J. F., Pollack J. B. and Ackerman T. P. (1983) Icarus, 57, 335-355 [6] Kopparapu, R.K. et al. (2013) ApJ 765, 131 [7] Yang, J. et al. (2014) ApJ 707, L2 [8] Wignall, P. (2001) Earth Science Reviews, 53 (1-2), 1-33 [9] Ernst R. E. et al. (2021) AGU Geophys. Mon. 255, pp. 3-26

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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