New competitive system for tomato's ripeness control
Bibliographic record
Abstract
ABSTRACT The tomatoes production shows a fast growing in the word. The need of fast industrial process to covert the high request of the second more consumed vegetarian produced after the potatoes, have attracted a considerable interest from both academia and industry. In this article, we develop a model based on high frequency structural simulator (HFSS) to evaluate different armatures of tomatoes for real time monitoring process. Unlike previous techniques, based on image processing, the proposed study presents a new approach of tomatoes evaluation. The tomatoes color may differ from side to another, which limits such solution. The proposed system uses the microwave penetration capability in order to perform 3D tomatoes evaluation. The sensitive of dielectric variation in terms of liquids composite of tomatoes, presents a new criteria for ripeness classification. The proposed model is simulated and experimentally approved for different kinds of tomatoes samples. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2901–2905, 2016
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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 | 0.000 | 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 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".