Bibliographic record
Abstract
Abstract In the present study, a new separation function T(x,α’,β) for the steady‐state screening process is presented. This new grade efficiency T(x,α’,β) presented here is a function of particle size x, separation sharpness α’, and the newly introduced separation efficiency β. With this new efficiency function, the screening classification process can be described exactly. Especially in the fine and coarse material ranges, a very good correlation of the calculated function with the measured values can be observed. A comparison of the grade efficiency function with separation sharpness α’, separation efficiency β, and only with the measure for separation efficiency has shown that the new grade efficiency T(x,α’,β) allows a significant improvement in the characterization of the stationary screen classification process. When compared with other models, the new model of the grade efficiency T(x,α’,β) shows a significantly higher correlation with the measured values and is therefore very well suited to describe a grade efficiency for the stationary screening process.
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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".