Information measure of absolute and relative quantification in double‐quantitative decision‐theoretic rough set model
Why this work is in the frame
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Bibliographic record
Abstract
The absolute and relative quantifications between the equivalence class and the target concept are the two important research endeavours in rough set theory. Double‐quantitative decision‐theoretic rough set (Dq‐DTRS) models utilise both absolute quantification and relative quantification in their upper and lower approximations to reflect the distinctive degrees of quantitative information. Herein, the authors apply the information theory to Dq‐DTRS model to characterise and measure these two types of quantitative information. The expressions of the information entropy with regard to the two quantifications and their corresponding information co‐entropy are presented in DqI‐DTRS model and DqII‐DTRSmodel, respectively. This work makes a further study of Dq‐DTRS models by discussing the information measures with respect to absolute and relative quantification.
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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 | 0.001 | 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 | 0.001 |
| 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