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Record W3092217717 · doi:10.5194/amt-14-1733-2021

Performance of open-path GasFinder3 devices for CH <sub>4</sub> concentration measurements close to ambient levels

2021· article· en· W3092217717 on OpenAlexaboutno aff
Christoph Häni, Marcel Bühler, A. Neftel, Christof Ammann, Thomas Küpper

Bibliographic record

VenueAtmospheric measurement techniques · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersBundesamt für UmweltAgroscope
KeywordsDispersion (optics)Environmental scienceLaserChemistryInverseAnalytical Chemistry (journal)Atmospheric sciencesPhysicsMathematicsEnvironmental chemistryOptics

Abstract

fetched live from OpenAlex

Abstract. Open-path measurements of methane (CH4) with the use of GasFinder systems (Boreal Laser Inc, Edmonton Canada) have been frequently used for emission estimation with the inverse dispersion method (IDM), particularly from agricultural sources. It is common to many IDM applications that the concentration enhancement related to CH4 sources is small, typically between 0.05 and 0.5 ppm, and accurate measurements of CH4 concentrations are needed at concentrations close to ambient levels. The GasFinder3-OP (GF3) device for open-path CH4 measurements is the latest version of the commercial GasFinder systems by Boreal Laser Inc. We investigated the uncertainty of six GF3 devices from side-by-side intercomparison measurements and comparisons to a closed-path quantum cascade laser device. The comparisons were made at near-ambient levels of CH4 (85 % of measurements below 2.5 ppm) with occasional phases of elevated concentrations (max. 8.3 ppm). Relative biases as high as 8.3 % were found, and a precision for half-hourly data between 2.1 and 10.6 ppm-m (half width of the 95 % confidence interval) was estimated. These results deviate from the respective manufacturer specifications of 2 % and 0.5 ppm-m. Intercalibration of the GF3 devices by linear regression to remove measurement bias was shown to be of limited value due to drifts and step changes in the recorded GF3 concentrations.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.132
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.040
GPT teacher head0.257
Teacher spread0.217 · 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 teacher head, not a consensus.

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

Citations14
Published2021
Admission routes1
Has abstractyes

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