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Record W2162490337 · doi:10.1021/ac048295c

Characterizing Dissolved Organic Carbon Using Asymmetrical Flow Field-Flow Fractionation with On-Line UV and DOC Detection

2005· article· en· W2162490337 on OpenAlex

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

VenueAnalytical Chemistry · 2005
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChemistryField flow fractionationDissolved organic carbonFractionationFlow (mathematics)Carbon fibersFlow injection analysisLine (geometry)Environmental chemistryChromatographyAnalytical Chemistry (journal)Detection limitMechanics

Abstract

fetched live from OpenAlex

A method of characterizing dissolved organic carbon (DOC) by asymmetrical flow field-flow fractionation with on-line UV and DOC detection is described and applied to standards and natural water samples. Poly(styrenesulfonate) polymer standards, Suwannee River humic standards, and naturally occurring surface water and groundwater DOC were analyzed using this coupled detection technique. Molecular weight determinations in the samples and standards were 6-30% lower with DOC analysis than UV analysis. This difference was attributed to the insensitivity of the latter technique to nonaromatic carbon and suggests the molecular weight determined with the DOC detector is a more accurate representation of the actual molecular weight of the DOC. A normalized intensity comparison (NIC) method was proposed to distinguish differences in the relative amounts of aromatic and aliphatic carbon in DOC by comparing the two detector responses. The NIC method was applied to yield an average aromatic content of the bulk DOC and to detail the aromatic content over a range of molecular weights in a single DOC fraction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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