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Record W2996013855 · doi:10.1029/2019je006357

Collision‐Induced Absorption of CH <sub>4</sub> ‐CO <sub>2</sub> and H <sub>2</sub> ‐CO <sub>2</sub> Complexes and Their Effect on the Ancient Martian Atmosphere

2020· article· en· W2996013855 on OpenAlexaff
Paul J. Godin, Ramses M. Ramírez, Charissa Campbell, Tyler Wizenberg, Tue Giang Nguyen, Kimberly Strong, John E. Moores

Bibliographic record

VenueJournal of Geophysical Research Planets · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsAtmosphere (unit)Bar (unit)Absorption (acoustics)Analytical Chemistry (journal)Mars Exploration ProgramAtomic physicsAbsorption spectroscopyAtmosphere of MarsSpectroscopySurface pressureIsotopologueChemistrySpectral lineMaterials sciencePhysicsMartianOpticsAstrobiologyThermodynamicsMeteorology

Abstract

fetched live from OpenAlex

Abstract Experimental measurements of collision‐induced absorption (CIA) cross sections for CO 2 ‐H 2 and CO 2 ‐CH 4 complexes were performed using Fourier transform spectroscopy over a spectral range of 150–475 cm −1 and a temperature range of 200–300 K. These experimentally derived CIA cross sections agree with the spectral range of the calculation by Wordsworth et al. (2017) however, the amplitude is half of what was predicted. Furthermore, the CIA cross sections reported here agree with those measured by Turbet et al. (2019, 2019). Additionally, radiative transfer calculations of the early Mars atmosphere were performed, and showed that CO 2 ‐CH 4 CIA would require surface pressure greater than 3 bar for a 10% methane atmosphere to achieve 273 K at the surface. For CO 2 ‐H 2 , liquid water is possible with 5% hydrogen and less than 2 bar of surface pressure.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations15
Published2020
Admission routes1
Has abstractyes

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