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Record W7160375047 · doi:10.29284/s6ygtk10

A Versatile Bioplastic Film Fabricated From Cocos Nucifera (Coconut Coir) In Guyana

2025· article· W7160375047 on OpenAlexaff
Vishal Mahabir, Patrick Ketwaru, Randy Sanichar

Bibliographic record

VenueInternational Journal of Advances in Signal and Image Sciences · 2025
Typearticle
Language
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCocos nuciferaCoirSodium hydroxideBioplasticUltimate tensile strengthCelluloseHemicelluloseLignin

Abstract

fetched live from OpenAlex

The coconut plant is an abundant crop stretching across all regions of Guyana in South America. The coconut coir is a cellulose-rich component of the coconut that can be converted into a versatile, biodegradable plastic film with thermomechanical properties comparable to single-use plastics on the world market. The hemicellulose and lignin content of the coconut coir was reduced by 56.5% and 71.7% respectively. An alkali/bleaching treatment of 8% sodium hydroxide (NaOH) and 8% sodium chlorite (NaClO2) solutions was found to be best. The pretreated coir produced uniform bioplastic films within 6-9 days after dissolution in trifluoroacetic acid (TFA). A 100% conversion of raw coir fibers into plastic film was achieved, with an ultimate tensile strength of 9.12 MPa. This bioplastic film is also thermally stable, starting to degrade at around 250 °C, similar to the degradation temperature of 97% cellulose-rich filter paper.

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 score0.002
Threshold uncertainty score0.003

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)0.0010.000

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 head0.007
GPT teacher head0.299
Teacher spread0.292 · 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
Published2025
Admission routes1
Has abstractyes

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