CERBF: a program for Radial basis function regression using Center-evolving algorithm
Why this work is in the frame
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Bibliographic record
Abstract
Radial basis function (RBF) is a simple and robust tool to build multivariable regression models. It follows machine learning techniques to automatically adjust its coefficients in the model through experiencing with sampling data. The predictive skill of RBF models is heavily dependent on the selection of RBF centers, which initially needs to be selected from the training data set. One difficulty to train a model using RBF for a large training data set is that the possible number of combinations of chosen centers is enormous, leading to large training time. The CERBF solves this problem by successively training models in randomly selected small subsets of the training set, while carrying over optimal centers found in one search, to the next one. CERBF training is significantly faster than going through all combinations of possible centers, with minimal impact on model accuracy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.009 | 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