Isotherms and Isosteric Heat Desorption of Hymenaea stigonocarpa Mart. Seeds
Bibliographic record
Abstract
The Brazilian Cerrado is one of the most important ecosystems and due to the extractivism it is necessary to recover the degraded areas. The tree of Hymenaea stigonocarpa Mart. is used in this reforestation system, so the study of post-harvest management of the seed is necessary for the propagation. The objective of this work was to determine the isotherms and the isosteric desorption heat of Hymenaea stigonocarpa Mart. Seeds, and to test the methodology of the Akaike’s information criterion (AIC) and Schwarz’s bayesian information criterion (BIC) for the choice of the best mathematical model. Different mathematical models were fitted to the experimental data and the model that best represents the phenomenon was selected, from the statistical parameters. To obtain the equilibrium moisture content was used static method using desiccants in incubators cameras with control of relative humidity by salt solution. The Oswin Modified model obtained better results according to analyzed parameters, being this model the one selected for prediction of the hygroscopic balance of the Hymenaea stigonocarpa Mart. seeds. It was found that the higher the temperature for the same equilibrium moisture content, the higher the water activity values. The AIC and BIC methodology contributed to the choice of the best mathematical model to predict the hygroscopicity phenomenon. The isosteric heat increased with the decrease in the equilibrium moisture content requiring a greater amount of energy to remove water from the seeds.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".