A Comparative Analysis of Ontario Cider Producers Information Sources and Production Practices
Bibliographic record
Abstract
An automated image analysis procedure was developed to determine extended filaments length and floc area to evaluate settling characteristics of activated sludge. Digitized image obtained by Gram staining granted the first step of algorithm, segmentation, to be extremely clear and simple. The image analysis work could become more accurate and less time consuming one to be required only 1 minute of operation time per image. Filamentous bulking phenomenon of the biological sludge was induced in a laboratory-scale bioreactor system under an extreme operational condition, and the non-bulking and filamentous bulking sludge samples captured were examined with image analysis as well as traditional settling test. There existed a linear relationship between DSVI (Diluted Sludge Volume Index) and the extended filaments length. Similar results were also obtained with the extended filaments per floc area. The arithmetic mean extended filaments length showed an excellent linearity with the DSVI. It is believed that the image analysis algorithm developed in this study can be utilized for estimation of the extended filaments length and for evaluation of the settling characteristics of activated sludge effectively.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".