Choice of segments in the B=B(H) approximation using spline functions
Bibliographic record
Abstract
In this paper we show how the choice of selected points for building the basic curve of the first magnetization can influence the accuracy. The presented approach enables one to simply build curves B = B (H) and μ = μ(H) using the cubic spline functions C(2). All procedures are practically given analytically, so that by having good information on the magnetic field at the beginning and at the end of a treated curve given by the couple (H,B), we obtain the curve twice differentiable. It is important to mention that we do not need to have many date points to construct all presented curves. Having the approximation of the curve B = B (H) and using the software package ‘CURVES’, it is possible to get much more information about the maximal value of the relative magnetic permeability, the differential permeability and the approximation of the curve μ = μ(H). This powerful software can be used separately for each calculation or, as the complete program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".