Determination of soil particle size distribution using computer analysis of microscopic images
Bibliographic record
Abstract
The project aims to develop a prototype device for determining the texture of soils and mineral deposits. The innovation of the designed solution consists in a significant reduction in the time of composition analysis with the possibility of any division into granulometric groups and the complete automation of the measurement from the moment the sample is introduced into the apparatus until the result is obtained. As part of the project, industrial research and experimental development are planned to be divided into the following stages: 1. Development of the measuring system. 2. Development of the structure and construction of device prototypes. 3. Development of the construction of the measuring system 4. Development of a mathematical model for processing data from the measuring system. 5. Preparation of software for device control and data recording. 6. Making the final prototype of the device. 7. Test tests of the final version of the device. The research will be conducted by a research consortium consisting of the project leader, i.e. Aumatic sp. z o.o. and the University of Agriculture in Krakow. The developed product will be intended for sale both on the domestic market and for export. Due to the number of entities potentially interested in the apparatus and the financial possibilities of potential recipients, the largest market should be developed countries (e.g. EU countries, USA, Canada, etc.). The main target groups of clients were: 1. Scientific institutions (universities, research institutes). 2. Institutions and enterprises performing analyzes for the needs of precision farming. 3. Chemical and Agricultural Stations. 4. Ceramic clay mining plants. 5. Manufacturers of ceramic products. 6. Laboratories conducting geotechnical tests for the needs of construction. 7. Laboratories carrying out environmental tests in the field of soil quality. 8. Provincial Inspectorates for Environmental Protection, Regional Directorates for Environmental Protection
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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 | 0.001 |
| 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".