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Record W4312293358 · doi:10.56530/lcgc.na.xh1183h9

Gaining New Insights in Advanced Polymeric Materials Using Comprehensive Two-Dimensional Liquid Chromatography

2022· article· en· W4312293358 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

VenueLCGC North America · 2022
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsDow Chemical (Canada)
Fundersnot available
KeywordsChemistryPolymerInstrumentation (computer programming)Flexibility (engineering)Raw materialCharacterization (materials science)NanotechnologyBiochemical engineeringChromatographyProcess engineeringComputer scienceOrganic chemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Two-dimensional liquid chromatography (2D-LC) offers new insights into modern polymeric materials such as biodegradable polymers, polymers made from renewable feedstock, and complex formulated systems. Advances in instrumentation and the development of new modulation techniques enable more combinations of different separation modes. Hyphenation with universal and information-rich detectors further enhances the versatility and flexibility of the analytical strategy. Detailed characterization of copolymer composition heterogeneity and identification of polymeric ingredients in complex consumer products are key highlights of new applications.

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 score0.068
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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