MétaCan
Menu
Back to cohort
Record W2247653350 · doi:10.1002/app.43351

Treatments of protein for biopolymer production in view of processability and physical properties: <scp>A</scp> review

2016· review· en· W2247653350 on OpenAlexafffund
Yicheng Du, Shuzhao Li, Yachuan Zhang, Curtis Rempel, Qiang Liu

Bibliographic record

VenueJournal of Applied Polymer Science · 2016
Typereview
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of ManitobaAgriculture and Agri-Food CanadaResearch ManitobaMinistry of Agriculture, Food and Rural Affairs
FundersAgriculture and Agri-Food CanadaCanola Council of Canada
KeywordsBiopolymerMaterials scienceMoisturePolymerBrittlenessPolymer scienceComposite materialBiochemical engineeringEngineering

Abstract

fetched live from OpenAlex

The development of bio‐based polymers from proteins has gained attention for their large availability and renewable and biodegradable nature. However, protein‐based plastics have limited commercial applications because of several drawbacks, such as poor processability, brittleness, moisture sensitivity, and inferior mechanical and thermal properties. Extensive studies have been conducted to solve or ameliorate these issues by pretreatment or modification of proteins or protein‐derived biopolymers before or during wet processing or dry processing at elevated temperatures. This review provides an overview of research efforts conducted in the area of physical and chemical treatment of proteins to achieve better processability, mechanical properties, and other physical performance based on a literature review in this subject. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 43351.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.283
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations29
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Applied Polymer ScienceSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207