Automated learning multi-criteria classifiers for FLIR ship imagery classification
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes an Automated Learning Method (ALM) based on Real-Coded Genetic Algorithm (RCGA) to infer the Multi-Criteria Classifiers (MCC) parameters. The Multi-Criteria Classifiers (or Multi-Criteria Classification Methods) considered are based on concordance and discordance concepts. A military database of 2545 Forward Looking Infra-Red (FLIR) images representing eight different classes of ships is therefore used to test the performance of these classifiers. The empirical results of MCC are compared with those obtained by other classifiers (e.g. Bayes and Dempster-Shafer classifiers). In this paper, we show the benefits of cross-fertilization of multi-criteria classifiers and information fusion algorithms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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