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Record W2145892124 · doi:10.1366/12-06798

Principles, Performance, and Applications of Spectral Reconstitution (SR) in Quantitative Analysis of Oils by Fourier Transform Infrared Spectroscopy (FT-IR)

2013· article· en· W2145892124 on OpenAlex
Diego L. García‐González, Jacqueline Sedman, F.R. van de Voort

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.

Bibliographic record

VenueApplied Spectroscopy · 2013
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsMcGill University
Fundersnot available
KeywordsDiluentDilutionAnalytical Chemistry (journal)ChemistryFourier transform infrared spectroscopyInfrared spectroscopySpectroscopyInfraredFourier transformAbsorption spectroscopyMatrix (chemical analysis)OpticsChromatographyThermodynamicsNuclear chemistry

Abstract

fetched live from OpenAlex

Spectral reconstitution (SR) is a dilution technique developed to facilitate the rapid, automated, and quantitative analysis of viscous oil samples by Fourier transform infrared spectroscopy (FT-IR). This technique involves determining the dilution factor through measurement of an absorption band of a suitable spectral marker added to the diluent, and then spectrally removing the diluent from the sample and multiplying the resulting spectrum to compensate for the effect of dilution on the band intensities. The facsimile spectrum of the neat oil thus obtained can then be qualitatively or quantitatively analyzed for the parameter(s) of interest. The quantitative performance of the SR technique was examined with two transition-metal carbonyl complexes as spectral markers, chromium hexacarbonyl and methylcyclopentadienyl manganese tricarbonyl. The estimation of the volume fraction (VF) of the diluent in a model system, consisting of canola oil diluted to various extents with odorless mineral spirits, served as the basis for assessment of these markers. The relationship between the VF estimates and the true volume fraction (VF(t)) was found to be strongly dependent on the dilution ratio and also depended, to a lesser extent, on the spectral resolution. These dependences are attributable to the effect of changes in matrix polarity on the bandwidth of the ν(CO) marker bands. Excellent VF(t) estimates were obtained by making a polarity correction devised with a variance-spectrum-delineated correction equation. In the absence of such a correction, SR was shown to introduce only a minor and constant bias, provided that polarity differences among all the diluted samples analyzed were minimal. This bias can be built into the calibration of a quantitative FT-IR analytical method by subjecting appropriate calibration standards to the same SR procedure as the samples to be analyzed. The primary purpose of the SR technique is to simplify preparation of diluted samples such that only approximate proportions need to be adhered to, rather than using exact weights or volumes, the marker accounting for minor variations. Additional applications discussed include the use of the SR technique in extraction-based, quantitative, automated FT-IR methods for the determination of moisture, acid number, and base number in lubricating oils, as well as of moisture content in edible oils.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.257
Teacher spread0.246 · 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