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Cellulose

2018· other· en· W4211231266 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

VenueEncyclopedia of Polymer Science and Technology · 2018
Typeother
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsCelluloseCellulosic ethanolCellophaneMicrocrystalline cellulosePolymer scienceChemical engineeringMaterials scienceChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This article covers nomenclature, sources, biosynthesis, preparation, uses, microcrystalline cellulose, structural chemistry, reactions, solvents, and liquid crystals. Cellulose for commercial purposes comes mostly from wood and cotton, whereas cellulose for research comes from bacteria, algae, and ramie (also a textile fiber). Preparation includes pulping and purification, with an alternative method of steam explosion. The pore structure of cellulose is mentioned. Emphasis is given to cellulose crystal structures. Cellulose solutions are important to the rayon and cellophane industries, and new solvents are of interest because they may lessen pollution and might permit commercial production of stronger cellulosic materials through the formation of liquid crystals. Common physical methods for assessment of cellulose structure are discussed. Figures include the chemical and physical structures of the molecule, sources of cellulose, biosynthesis charts, molecular weight distributions, crystallite sizes, X‐ray diffraction patterns, nuclear magnetic resonance spectra, conformational energy plots, and the unit cell structures of cellulose I–IV.

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 categoriesScience and technology studies, 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: Other · Consensus signal: Other
Teacher disagreement score0.070
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.267
Teacher spread0.259 · 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