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Record W3111772599 · doi:10.17975/sfj-2020-007

PAPER STRAWS: AN INVESTIGATION INTO SURFACE MODIFICATION AND HYDROPHOBIZATION OF CELLULOSE

2020· article· en· W3111772599 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

VenueSTEM Fellowship Journal · 2020
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsContact angleSilanolSolventTolueneSilylationCelluloseMaterials scienceLeaching (pedology)Chemical engineeringChemistryPolymer chemistryComposite materialOrganic chemistryCatalysisEnvironmental science

Abstract

fetched live from OpenAlex

In order to improve the quality of paper straws, experiments involving the hydrophobization of paper, in a silylation reaction with chloro(dimethyl)octadecylsilane using various solvents, were conducted. The ImageJ program was used to quantify hydrophobicity by calculating the contact angle between a water droplet and a small piece of paper, which were compared between treatment groups as well as with untreated paper and plastic straws. Samples were exposed to a variety of liquids in one-hour periods for a total of six hours. After each hour, contact angle measurements were taken. Results suggested that hydrophobicity declines with time due to leaching of silanol from the treated paper. Contact angles between water droplets and the treated paper remained larger than that of untreated paper straws throughout testing, indicating higher hydrophobicity. Furthermore, samples that were silylated using dioxane as a solvent were better able to maintain hydrophobicity than samples silylated using toluene as a solvent.

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)0.001
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 score0.008
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.055
GPT teacher head0.296
Teacher spread0.241 · 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