Studying Factors in the Utilization of Sansevieria stuckyi God.-Leb. Fibers to Create Products with Environmentally Friendly Processes
Bibliographic record
Abstract
The objective of this research was to study the utilization and physical properties of Sansevieria stuckyi God.-Leb.This was a mixed-methods study conducted using a structured questionnaire having a high reliability score (Cronbach's alpha = 0.936).According to the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), four significant factors were revealed, e.g., 1) utility, 2) perception, 3) sales motivation, and 4) eco-friendly materials.These factors affect the efficiency in the creation of fiber-based textile products.The results of this research generated a process for the recycling of numerous local wastes for economic value added of the involved communities and establishment of the guidelines on utilizing Sansevieria stuckyi God.-Leb.to create textile products with an eco-friendly process.This will generate a body of knowledge and understanding of how to develop textile products that meet consumer needs.In addition, the results of this research will motivate textile product designers to apply their local plants in textile product creation in order to meet the needs of community inhabitants appropriately and to demonstrate their collective responsibility for the global environment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".