MétaCan
Menu
Back to cohort
Record W2118846430 · doi:10.5539/jmsr.v2n1p23

Evaluation of Inter-fiber Bonding in Wood Pulp Fibers by Chemical Force Microscopy

2012· article· en· W2118846430 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Materials Science Research · 2012
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of New BrunswickFPInnovations
Fundersnot available
KeywordsMaterials sciencePulp (tooth)Composite materialvan der Waals forceFiberAtomic force microscopyCellulose fiberBond strengthAdhesionMoleculeNanotechnologyAdhesiveLayer (electronics)

Abstract

fetched live from OpenAlex

Atomic force microscopy with chemically modified tips was used to evaluate the inter fiber bonding properties of typical wood pulp fibers. Using –OH functionalized AFM tips as a model of cellulosic pulp fiber surfaces, pull-off forces and work of adhesion were measured in aqueous media. Three distinct tip-surface interactions were identified from force-displacement curves, representing three typical surface conditions of wet pulp fiber surfaces: solid, swollen and micro-fibrillated. The work of adhesion calculated shows that van der Waals forces are the major contributing factor on non-swollen solid regions of fiber surfaces. The difference in inter-molecular bond strength of different pulp fibers is relatively small. The inter-fiber bonding properties of pulp fibers are mainly controlled by the surface deformability, which determines the area of molecular contact at fiber-fiber physical interaction points.

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)0.014
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.074
GPT teacher head0.412
Teacher spread0.338 · 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