ANÁLISE DA UTILIZAÇÃO DE MODELOS DIFUSIVOS NA SECAGEM DE PIMENTA-DO-REINO PRETA (Piper nigrum L.)
Bibliographic record
Abstract
A pimenta do reino preta é a mais importante especiaria comercializada mundialmente, sendo o Brasil um dos maiores produtores. Mesmo assim, poucos estudos para otimização do processo produtivo dessa commodity foram realizados. O objetivo desse trabalho foi realizar a caracterização da pimenta do reino e analisar a cinética de secagem. Com umidades variadas, mediram-se as dimensões lineares (diâmetro de Sauter e diâmetro médio), da área superficial, volume, esfericidade, e ainda a massa específica aparente e porosidade dos grãos. Os experimentos de cinética de secagem foram realizadosem camada fina, em um secador de convecção forçada com temperatura variando de 50 a 70ºC, e com velocidade do ar de 2,0 e 4,0 m/s. Com esses dados, fizeram-se ajustes das equações de Lewis, Page e Overhults, e do modelo Difusivo com hipóteses simplificadoras para a difusividade. Os resultados obtidos mostram que o modelo difusivo foi o mais adequado.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".