A new super-efficiency directional distance function model in the presence of negative data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The super-efficiency range directional model (SRDM) has been developed to address the limitations of the classic super-efficiency model of the directional distance function (DDF) in handling negative data under the premise of variable returns to scale (VRS). Although the SRDM model can identify efficiency in the presence of negative data, it suffers from infeasibility. This study introduces enhancements to the SRDM model. By analyzing the direction of the SRDM model, the adjustment range of the base point is established, and the new direction is obtained, so as to reduce the occurrence of infeasible. This modification is based on the direction of the SRDM model, and the super-efficiency DDF model under the new direction can both handle negative data while avoiding infeasibility when the base point can be adjusted.
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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 | 0.014 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 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