An Analytic Hierarchy Process for Bit Optimization Based on the Fractal Crushing Work Ratio
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Bibliographic record
Abstract
The paper presents a new method of bit optimization by applying index scale AHP (Analytic Hierarchy Process). It constructs judgment matrix based on the complete consistency principle. For the matrix has the consistency of the importance and transitivity, it simplifies the process of calculation by cancelling the consistency checking process, which is used in the traditional AHP. The adjacent important ratio is selected by combining hierarchical thought and fractal dimension, and the effect of adjacent important ratio disturbance on the optimization result is reduced. The accuracy of the decision result of bit optimization hierarchical structure model is ensured effectively, and the stability and flexibility of the model is enhanced. The model can be applied in different regions based on actual needs, and to solve optimization problems of different types of drill bit. Key words: Crushing work ratio; Index scale; Bit optimization
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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 | 0.002 |
| 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 it