Efficient Approximation Using Probabilistically Improved Combinatorial Structure of Bernstein's Polynomial Operator's Weights through the Fusion of Dual-Perspectives
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Bibliographic record
Abstract
A new polynomial approximation operator has been proposed which uses weight-functions of the well-known Bernstein’s Polynomial operator in its probabilistically improved combinatorial structure, achieved through a rather-ingenious ‘Fusion’ of two dual perspectives. These weights are functions of the impugned variable of the unknown function being approximated, and are not mere constants. The new approximation formula has been compared empirically with the simple classical method of polynomial approximation using the well-known “Bernstein Operator”. The percentage absolute relative errors for the proposed approximation formula and that with the “Bernstein Operator” have been computed for certain selected functions and with different number of node points in the interval of approximation. It has been observed that the proposed approximation formula produces exceedingly-significantly better results.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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