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Record W7117456046 · doi:10.29132/ijpas.1666550

Green Synthesis of Glycerol-Plasticized Chitosan Biofilms Containing Macerated St. John's Wort Oil

2025· article· W7117456046 on OpenAlexaboutno aff
Hatice Karaer Yağmur

Bibliographic record

VenueInternational Journal of Pure and Applied Sciences · 2025
Typearticle
Language
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsnot available
Fundersnot available
KeywordsSwellingBiofilmPorosityVolume (thermodynamics)Degradation (telecommunications)Chitosan

Abstract

fetched live from OpenAlex

Abstract: In this study, St. John's Wort oil was obtained by maceration, a tradi-tional method, using olive oil macerate. St. John's Wort oil was added to chi-tosan-based biofilms as an additive, and chitosan-based biofilms containing chi-tosan/St. John's Wort oil (SJWO) were obtained. Biofilms were characterized by FTIR. The preparation and physical potential use of these films are presented. The porosity, swelling capacity, thickness, degradation rates, pore volumes and opacity of biofilms were determined. It was observed that as the amount of oil entering the structure increased, the thickness of the film increased and its swelling properties decreased. The thickness and opacity of CN/SJW-0.2, CN/SJW-0.6 and CN/SJW-0.8 biofilms were determined as 0.17, 0.28 and 0.30 mm and 1.21, 0.98 and 0.94, respectively. It was determined that increasing the amount of SJWO in-creased the film thickness and decreased its opacity. The pore volume (Vp) values of CN/SJW-0.2, CN/SJW-0.6, and CN/SJW-0.8 were calculated as 0.098, 0.0085 and 0.0086. The porosity values of the films CN/SJW-0.2, CN/SJW-0.6 and CN/SJW-0.8 were determined as 0.01952, 0.00172 and 0.00175 re-spectively.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.012
GPT teacher head0.274
Teacher spread0.261 · 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.

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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