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Record W1983433437 · doi:10.1021/ac030093d

Electrospray-Mass Spectrometric Analysis of Reference Carboxylic Acids and Athabasca Oil Sands Naphthenic Acids

2003· article· en· W1983433437 on OpenAlex
Chun Chi Lo, Brian G. Brownlee, Nigel J. Bunce

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.

Bibliographic record

VenueAnalytical Chemistry · 2003
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of GuelphEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Water NetworkNational Water Research Institute
KeywordsNaphthenic acidChemistryOil sandsElectrosprayMass spectrometryElectrospray ionizationCarboxylic acidChromatographyTailingsMass spectrumAsphaltEnvironmental chemistryAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

Naphthenic acids (NAs) are complex mixtures of naturally occurring acyclic and cyclic aliphatic carboxylic acids that are responsible for the toxicity of the water in the tailings ponds associated with the recovery of bitumen from the Athabasca oil sands. NAs are difficult to analyze due to their complexity and the lack of commercially available NA standards. This paper describes the use of negative ion electrospray ionization mass spectrometry for the analysis of NAs. Model carboxylic acids, alone and in mixture, afforded mass spectral signal intensities that were highly dependent on extractor and cone voltages and on molecular structure. These effects were also observed for authentic NAs. Under conditions that were close to optimal for all the model compounds, their calibration sensitivities varied by a factor of <2, and there were minimal interactions when the model compounds were examined in mixture. Under the same conditions, the authentic NAs showed apparent congener distributions similar to those observed previously by GC/MS for derivatized NAs. The similar calibration sensitivities among congeners allowed the use of the standard addition method to determine the approximate absolute concentrations of NA congeners in an authentic sample.

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)0.001
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 score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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