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Using Lignin to Modify Starch-Based Adhesive Performance

2020· article· en· W2997362670 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemEngineering · 2020
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsBC Research (Canada)University of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLigninAdhesiveSlurryPaperboardWet strengthStarchMaterials scienceComposite materialWater resistanceChemical engineeringKraft paperChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Unmodified kraft lignin was used to create a starch-based adhesive via the Stein Hall process. Lignin up to 35 wt% was used in several formulations. Lignin was incorporated in both the carrier and slurry portions of the formulations and the effect on adhesive strength and water resistance was studied. The addition of lignin resulted in a significant increase in adhesive strength when the lignin was added solely to the slurry portion. When lignin was added solely to the carrier portion, the adhesive strength decreased. Other formulations, where lignin was present in both the carrier and slurry portions, showed moderate increases in adhesive strength. Finally, the addition of lignin increased the water-resistance of the adhesive bond in the paperboard.

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 score0.005
Threshold uncertainty score0.971

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 head0.035
GPT teacher head0.220
Teacher spread0.185 · 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