Comparison and Analysis of Non-Linear Least Squares Methods for 3-D Coordinates Transformation
Why this work is in the frame
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Bibliographic record
Abstract
AbstractFour different methods are evaluated by solving the Molodensky 3-D coordinate transformation problem. These methods are Steepest Descent, Trust region, Gauss Newton and Levenberg-Marquardt. Also, the problem has been solved using the traditional combined least-squares adjustment. The solutions of these methods are compared by the number of iterations required for the objective function to converge to its minimum value. Externally, the RMSE of the transformed check stations of the geodetic network (curvilinear coordinates) are compared to the RMSE obtained by transforming the same set of check stations using the transformation parameters recommended by the Egyptian Survey Authority.Keywords: COORDINATE TRANSFORMATIONOPTIMISATION PROCEDURESNATIONAL GEODETIC NETWORKSWGS84
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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