The effect of natural fillers on the marine biodegradation behaviour of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)
Bibliographic record
Abstract
Worldwide, improper disposal of plastics is instigating environmental initiatives to combat plastics accumulation of in the environment and the world's oceans. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) biocomposites with Miscanthus (Misc) fibres and distillers' dried grains with solubles (DDGS) were studied to ascertain if natural fibres and proteinaceous fillers can improve polyhydroxyalkanoate marine biodegradability. Using ASTM standard D7991-15, the biodegradation of PHBV, PHBV with Misc (15 and 25 wt%) and PHBV with DDGS (15 and 25 wt%) was performed in a simulated marine environment for the first time, as indicated by a literature survey. PHBV/Misc (85/15) and (75/25) biocomposites showed 15 and 25% more biodegradation compared to PHBV, respectively. Proteinaceous PHBV/DDGS (85/15) and (75/25) biocomposites showed 17 and 40% more biodegradation compared to PHBV, respectively. Furthermore, PHBV/Misc (75/25) and PHBV/DDGS (75/25) biocomposites were marine biodegraded in 412 and 295 days, respectively. In conclusion, proteinaceous fillers (DDGS) biocomposites have better marine biodegradability than miscanthus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".