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Record W2808421621 · doi:10.1080/00397911.2018.1465096

Synthetic modifications of chitin and chitosan as multipurpose biopolymers: A review

2018· review· en· W2808421621 on OpenAlexaff
Muhammad Aamir Sajid, Sohail Anjum Shahzad, Fatima A. Hussain, W. G. Skene, Zulfiqar Ali Khan, Muhammad Yar

Bibliographic record

VenueSynthetic Communications · 2018
Typereview
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsBombardier (Canada)Université de Montréal
FundersGovernment College University, LahoreHigher Education Commision, PakistanHigher Education Commission, Pakistan
KeywordsChitinChitosanChemistryBiomaterialBiodegradationBiopolymerReactivity (psychology)Polymer scienceOrganic chemistryNanotechnologyPolymerMaterials science

Abstract

fetched live from OpenAlex

Chitin and chitosan are well-thought-out multipurpose biopolymers. Chitosan which is deacetylated chitin is useful than chitin and is biomaterial of great interest. Regardless of its biodegradability, chemical modifications suggest due to the amino side reactivity, helps to impart it other great qualities. Herein, we discuss the preparative methods of synthetically modified derivatives, some are commercially available. This review shields the literature from last few decades.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.363
Teacher spread0.300 · 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 designNot applicable
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

Citations27
Published2018
Admission routes1
Has abstractyes

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