MétaCan
Menu
Back to cohort
Record W2346773930 · doi:10.1016/j.jqsrt.2016.04.025

New and improved infra-red absorption cross sections and ACE-FTS retrievals of carbon tetrachloride (CCl4)

2016· article· en· W2346773930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Quantitative Spectroscopy and Radiative Transfer · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Waterloo
FundersCanadian Space AgencyNational Oceanic and Atmospheric AdministrationNational Centre for Earth ObservationNatural Environment Research CouncilSight Research UK
KeywordsHITRANStratosphereCarbon tetrachlorideEnvironmental scienceRemote sensingAbsorption (acoustics)InfraredAtmospheric sciencesMaterials scienceMeteorologyAbsorption spectroscopyChemistryPhysicsOpticsGeology

Abstract

fetched live from OpenAlex

Carbon tetrachloride (CCl4) is one of the species regulated by the Montreal Protocol on account of its ability to deplete stratospheric ozone. As such, the inconsistency between observations of its abundance and estimated sources and sinks is an important problem requiring urgent attention (Carpenter et al., 2014) [5]. Satellite remote-sensing has a role to play, particularly limb sounders which can provide vertical profiles into the stratosphere and therefore validate stratospheric loss rates in atmospheric models.This work is in two parts. The first describes new and improved high-resolution infra-red absorption cross sections of carbon tetrachloride/dry synthetic air over the spectral range 700-860cm-1 for a range of temperatures and pressures (7.5-760Torr and 208-296K) appropriate for atmospheric conditions. This new cross-section dataset improves upon the one currently available in the HITRAN and GEISA databases. The second describes a new, preliminary ACE-FTS carbon tetrachloride retrieval that improves upon the v3.0/v3.5 data products, which are biased high by up to ~20-30% relative to ground measurements. Making use of the new spectroscopic data, this retrieval also improves the microwindow selection, contains additional interfering species, and utilises a new instrumental lineshape; it will form the basis for the upcoming v4.0 CCl4 data product.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.271
Teacher spread0.255 · 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