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Record W4409741149 · doi:10.1088/1361-6501/add033

Utility of ammonium salts for the calibration of NH<sub>3</sub> sensors

2025· article· en· W4409741149 on OpenAlexafffund
Joseph Brent Edvin Saharchuk, Mohamed Faizal Abdul-Careem, Hans D. Osthoff

Bibliographic record

VenueMeasurement Science and Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalibrationAmmoniumEnvironmental scienceComputer scienceAnalytical Chemistry (journal)Materials scienceEnvironmental chemistryProcess engineeringChemistryMathematicsStatisticsOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract The calibration of NH 3 -sensing instruments has been an ongoing challenge to atmospheric chemists. Here, the potential utility of ammonium nitrate (NH 4 NO 3 ), -sulfate ((NH 4 ) 2 SO 4 ), -bisulfate (NH 4 HSO 4 ), -carbonate ((NH 4 ) 2 CO 3 ), and -bicarbonate (NH 4 HCO 3 ) to generate gas streams containing NH 3 or aerosol NH 4 + calibrated by measuring the co-emitted acids was investigated. Head space vapors and aerosols were analyzed using a commercial total nitrogen (N t ) instrument modified to quantify N t mixing ratios in both the gas- and particle phases, scanning mobility particle sizing, thermal-dissociation cavity ring-down spectroscopy, and Fourier transform infrared spectroscopy. The best results were obtained with NH 4 HCO 3 . Using a simple gas delivery setup consisting of two dilution stages and a line heater, the NH 3 output from NH 4 HCO 3 was calibrated by quantifying the stoichiometric co-emission of CO 2 with a relatively inexpensive non-dispersive infrared spectrometer. The new approach constitutes a viable alternative to conventional NH 3 cylinder calibration setups.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.230
Teacher spread0.211 · 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
Published2025
Admission routes2
Has abstractyes

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