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Record W4214745438 · doi:10.5194/amt-11-5827-2018

New and improved infrared absorption cross sections for trichlorofluoromethane (CFC-11)

2018· article· en· W4214745438 on OpenAlexaboutno aff
Jeremy J. Harrison

Bibliographic record

VenueAtmospheric measurement techniques · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNational Centre for Earth ObservationNatural Environment Research CouncilSight Research UK
KeywordsHITRANSpectral resolutionInfraredChemistryTroposphereSpectral lineAnalytical Chemistry (journal)Absorption spectroscopyAtmospheric sciencesOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract. Trichlorofluoromethane (CFC-11), a widely used refrigerant throughout much of the twentieth century and a very potent (stratospheric) ozone-depleting substance (ODS), is now banned under the Montreal Protocol. With a long atmospheric lifetime, it will only slowly degrade in the atmosphere, so monitoring its vertical concentration profile using infrared-sounding instruments, and thereby validating stratospheric loss rates in atmospheric models, is of great importance; this in turn requires high-quality laboratory spectroscopic data. This work describes new high-resolution infrared absorption cross sections of trichlorofluoromethane/dry synthetic air over the spectral range 710–1290 cm−1, determined from spectra recorded using a high-resolution Fourier transform spectrometer (Bruker IFS 125HR) and a 26 cm pathlength cell. Spectra were recorded at resolutions between 0.01 and 0.03 cm−1 (calculated as 0.9/MOPD; MOPD: maximum optical path difference) over a range of temperatures and pressures (7.5–760 Torr and 192–293 K) appropriate for atmospheric conditions. This new cross-section dataset improves upon the one currently available in the HITRAN (HIgh-resolution TRANsmission) and GEISA (Gestion et Étude des Informations Spectroscopiques Atmosphériques) databases through an extension to the range of pressures and temperatures, improved signal-to-noise and wavenumber calibrations, the lack of channel fringing, the better consistency in integrated band intensities, and additionally the coverage of the weak combination band ν2+ν5.

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)0.001
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.026
GPT teacher head0.257
Teacher spread0.231 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

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