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Record W4232236240 · doi:10.32920/ryerson.14649030

Production of Bioplastics from Renewable and Sustainable Feedstock Resources

2021· preprint· en· W4232236240 on OpenAlexaff
Ahmad Chaudhry

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRalstoniaBioplasticRaw materialAutoclaveHydrolysisEnzymatic hydrolysisSugarYield (engineering)Pulp and paper industryFood scienceChemistryEnzymeMaterials scienceOrganic chemistryWaste managementComposite material

Abstract

fetched live from OpenAlex

This study illustrates the potential opportunity for the utilization of hemp to produce PHB (poly(3-hydroxybutyrate). The objective of the study was to optimize simple sugar availability from hemp for Ralstonia eutropha. The use of three pre-treatment methods (grinded – 5% NaOH – Autoclave at 121 oC for 60 minutes) was able to provide a better fractional insoluble solids (FIS) of ≃ 61 % that was significantly better compared to other combinations of pre-treatments studied. Optimum enzyme dosage was also determined by comparing different enzyme concentrations and found that three enzymes should contain a dose of 1.5 g /L. The optimum pretreatment and hydrolysis conditions resulted in a better enzyme hydrolysis yield of 10.9 % and PHB yield of ≃ 43 %. Results also demonstrate that sonification did not improve PHB recovery, while pH control increased PHB recovery. Keywords: Hemp, Ralstonia eutropha, PHB, Pre-treatment, Enzyme Hydrolysis

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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