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Record W2123294491 · doi:10.1002/app.38911

Characterization of soda hardwood lignin and the formation of lignin fibers by melt spinning

2013· article· en· W2123294491 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

VenueJournal of Applied Polymer Science · 2013
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLigninHardwoodMaterials scienceSoftwoodFiberSpinningChemical engineeringCharacterization (materials science)PolymerMelt spinningRheologyComposite materialPolymer scienceOrganic chemistryChemistryBotanyNanotechnology

Abstract

fetched live from OpenAlex

Abstract Lignin fibers were developed from a commercial available soda hardwood lignin (SHL) with a melt‐spinning approach. SHL showed spinnability to form the fine fibers when poly(ethylene oxide) was used as a plasticizer with lignin. The thermal properties of lignin provided valuable information to assist the processing steps of the lignin fiber formation. The guaiacyl/syringyl ratio in SHL was determined by 31 P‐NMR because it had great influence on the thermal mobility of lignin. A suitable temperature profile for the melt spinning was predicted through rheological studies of lignin. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.214

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 head0.002
GPT teacher head0.166
Teacher spread0.163 · 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