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Record W2136666341 · doi:10.1039/c3cp53543f

Red-light initiated atmospheric reactions of vibrationally excited molecules

2013· article· en· W2136666341 on OpenAlexafffund
Veronica Vaida, D. J. Donaldson

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsExcited stateOvertoneChemistryPhotochemistryAtmospheric chemistryAtmosphere (unit)MoleculeTrace gasExcitationWavelengthAtomic physicsChemical physicsOzoneMeteorologySpectral linePhysicsOrganic chemistryOptics

Abstract

fetched live from OpenAlex

We present a brief review of long wavelength, red-light initiated chemistry from excited vibrational levels of the ground electronic state of atmospheric trace species. When sunlight driven electronic state reactions are not effective, photochemical processes occurring by vibrational overtone excitation have been found to be important in reactions of oxidized atmospheric compounds (acids, alcohols and peroxides) prevalent in the Earth's atmosphere. This review focuses on the fundamental energetic, mechanistic and dynamical aspects of unimolecular reactions of vibrationally excited atmospheric species. We will discuss the relevance of these red light initiated reactions to address the discrepancies between atmospheric measurements and results of standard atmospheric models.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.211
Teacher spread0.200 · 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 designBench or experimental
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

Citations38
Published2013
Admission routes2
Has abstractyes

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