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Record W2972640066 · doi:10.5194/amt-2019-298

Technical note: Common glitch affecting the EC/OC split point determination in the Sunset Thermal-Optical Analyzerand recommendations to reduce its occurrence

2019· article· en· W2972640066 on OpenAlexafffund
S. Gagné, Brett Smith, Gregory J. Smallwood, Joel C. Corbin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsNational Research Council Canada
FundersNatural Resources Canada
KeywordsGlitchClassification of discontinuitiesDiscontinuity (linguistics)TransmittanceOpticsFilter (signal processing)SunsetThermalSpectrum analyzerPoint (geometry)Materials scienceEnvironmental sciencePhysicsMathematicsEngineeringElectrical engineeringMeteorologyGeometry

Abstract

fetched live from OpenAlex

Abstract. We identified a common and relatively frequent glitch in the light transmittance/reflectance measurement during thermal-optical analysis in the Sunset Laboratory bench top thermal-optical analyzer models. In the instrument studied, the glitch is observed for one in three punch analyses when using the default analysis parameters. The occurrence of this glitch can invalidate the split point and thus the OC and EC fractions and absolute quantities reported. The glitch was observed in data from at least three independent laboratories using different thermal protocols. We describe this glitch as a “discontinuity” (rapid increase or decrease occurring over a few seconds) in the laser transmittance or reflectance which happens relatively frequently and whose behaviour varies in amplitude, timing and direction. We use over 2,200 filter-punch analyses to expose the factors that contribute to the risk of such a discontinuity occurring. We demonstrate that these discontinuities are due to the movement of filter punches within the instrument, and can therefore be minimized by decreasing the blower speed of the instrument and, if possible, by ensuring a tighter fit of the filter punch in its holder (by testing different spoons). The decrease in blower speed has a negligible effect on the measured temperature program during analysis and is the single most effective way to reduce the risk of discontinuity occurrence. We recommend these modifications for all Sunset instruments.

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 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 score0.359
Threshold uncertainty score0.335

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 communication0.0000.000
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 head0.026
GPT teacher head0.303
Teacher spread0.277 · 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.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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