An Overview of Bioplastic Research on Its Relation to National Policies
Bibliographic record
Abstract
There is an increasing concern about fossil energy and products derived from it. The plastic industry depends on oil, and produced plastics cannot degrade naturally. An alternative to plastics from oil is the use of bioplastics, which can be degradable. The bibliometric study of the publications related to bioplastics carried out in this paper shows that research on this topic is growing both in developed (USA, European Union, and Canada) and in developing countries (China, India, Thailand, and Malaysia), mostly following the implementation of bioeconomy standards and labels by their governments. The main authors and the collaborations they have worldwide are also presented here. The research carried out in this paper is not only devoted to technological aspects but also to economic aspects and inhabitant ratios. Trends in publications, by country and authors, are analyzed. Finally, this paper also studies the countries governmental policies and how they impact the bioplastic field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".