Bibliographic record
Abstract
© Sa majesté la reine, représentée par le ministre de la Défense nationale, 2005 Following user defined paths and seeking goal locations is fundamental to Autonomous Unmanned Ground Vehicle (UGV) navigation. This paper summarizes the current state of the art in robotic path tracking for Ackerman steered vehicles and presents results of implementation and adaptation of the Pure Pursuit algorithm at Defence R&D Canada – Suffield. Résumé La poursuite de parcours configurés par l’utilisateur et la recherche de la location des buts sont fondamentales à la navigation autonome des Véhicules terrestres sans pilotes (UGV). Cet article résume l’état actuel de l’art de localiser des parcours avec la robotique en utilisant des véhicules munis d'un système de direction reposant sur le principe Ackerman et présente l’implémentation et l’adaptation de l’algorithme Pure Pursuit à R & D pour la défense Canada – Suffield. DRDC Suffield TM 2005-224 i This page intentionally left blank. ii DRDC Suffield TM 2005-224
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.516 | 0.446 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".