Production and Characterization of Bio-Briquettes from the Cassava Stems and Bamboo Charcoal Bonded with Organic Adhesive
Bibliographic record
Abstract
This study aimed to determine the effects of a materials combination used by the waste biomass of bamboo and cassava stem mixed with a tapioca adhesive on the quality of charcoal briquettes.The briquettes were made with a combination of the raw materials between the cassava stem and bamboo of 75%:25%, 50%:50%, and 25%:75%.Then, the used charcoal materials were mixed with three tapioca concentrations of 8%, 10%, and 12%.The characteristics of the charcoal briquettes, such as density, moisture content, shatter resistance index, calorific value, combustion rate, and compressive strength were observed.The charcoal briquettes with a high percentage of bamboo combination showed to increase the calorific value and the compressive strength but decreased the rate of combustion.In contrast, the low concentration of tapioca glue increased the density, compressive strength, and shatter resistance index but decreased the combustion rate.It was revealed that the used material combination and the adhesive content affected various properties of charcoal briquettes.Therefore, it can be suggested that the materials combination of bamboo and cassava stems waste can be utilized for making briquettes with a low percentage of tapioca adhesive.
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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".