Study of Package Design for a Craft Wooden Boat Model Using Corrugated Board and Natural Extract to Prevent Termites
Bibliographic record
Abstract
The objectives of this research were to study and design packaging, test its efficiency, and determine the satisfaction levels of consumers with the structure and graphic design of a craft wooden boat model packaging produced from corrugated board using natural extract to prevent termites. Data collection was conducted using focus groups of producers and consumers. Data was then summarized and used for the design and creation of the model packaging. Suggestions from experts were applied to improve the packaging of the craft wooden boat model; its preventive efficiency was then tested and the satisfaction of consumers was assessed. The results of the package structure test showed that bursting strength was 8.66 kgf/cm2, edge crush test was 3.86 kg/cm and drop height was 762 mm, which reaches standards ASTM D 774, ISO 3037 and ASTM D 5276, as well as helping prevent termites from biting. The size and design were portable and suitable to be displayed for sale. Concerning graphic design, a unique lined pattern narrating the story of a river of time that united the lifestyles of Thai people living along the river in the olden days, was created and combined with other design details to convey an impression of the product inside. Survey results revealed that customers were highly satisfied (=4.09, S.D. = 0.60) with the craft wooden boat model package in terms of functionality and marketing.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".