Performance Evaluation Within CASE_ATTI of MHT and JVC Association Algorithms for COMDAT TD
Bibliographic record
Abstract
Abstract : Command Decision Aid Technology (COMDAT) is a Technology Demonstrator Project (TDP) scheduled to take place during the June 2000 to March 2007 time frame. COMDAT aims to form the basis for defining the mid-life upgrade to the Command and Control Information System (C2IS) of the HALIFAX Class frigate. The overall TD program consists of developing an integrated Maritime Tactical Picture (MTP), which is being achieved through three development cycles. Defence Research & Development Canada (DRDC) Valcartier is a partner in the COMDAT project, whose part of the contribution consists of performing an independent analysis of sea trial data to assess the performance of the MSDF technology compared the legacy Command & Control System (CCS), conducting a sensitivity analysis of COMDAT MSDF parameters and algorithms to recommend improvements for COMDAT subsequent cycles, and providing scientific advises for Multi-Sensor Data Fusion (MSDF) technology where required. This report presents the work performed under the sensitivity analysis task. The main objective of this task consists of evaluating a candidate alternative to the Jonker, Volgenant & Castanon (JVC) association algorithm, that is used by COMDAT MSDF. This candidate is the Multiple Hypothesis Tracking (MHT) association algorithm, an implemented version of which is available in DRDC Valcartier's Concept Analysis and Simulation Environment for Automatic Target Tracking and Identification (CASE ATTI) test-bed. The report presents a comparison of the two algorithms. This comparison was motivated by a performance evaluation of COMDAT MSDF in which association performance was not as good as expected.
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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 | 0.006 | 0.020 |
| 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 | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".