{"id":"W3020207422","doi":"10.1109/csci49370.2019.00079","title":"Recognition of Drone Formation Intentions Using Supervised Machine Learning","year":2019,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Drone; Computer science; Softmax function; Artificial intelligence; Machine learning; Identification (biology); Support vector machine; Plan (archaeology); Computer security; Deep learning; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000541031,0.00005238117,0.0001005435,0.0001028014,0.0000462115,0.00003439038,0.0001452603,0.00002712837,0.00007382302],"category_scores_gemma":[0.00005223681,0.00004738649,0.00004705973,0.0002527923,0.000008087619,0.0007182547,0.0000585798,0.00007894912,0.00004877597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001554194,"about_ca_system_score_gemma":0.00001550124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007032224,"about_ca_topic_score_gemma":0.00001682811,"domain_scores_codex":[0.9993404,0.0001133119,0.0001815016,0.0001166235,0.0001474163,0.0001007583],"domain_scores_gemma":[0.9995562,0.00006701192,0.00007893743,0.0001634339,0.000114806,0.00001965116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001995356,0.0001410842,0.05659194,0.0001848056,0.00004458075,0.000002059862,0.001401345,0.003457888,0.3486665,0.007297577,0.00002268559,0.5821695],"study_design_scores_gemma":[0.0003651619,0.00007469455,0.005641514,0.00004833321,0.000004253463,0.000013258,0.00005642457,0.9597431,0.03166338,0.002164795,0.0001205284,0.0001045433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3382101,0.000018961,0.6589953,0.00005102457,0.0001173986,0.00005920218,5.951442e-7,0.00006047209,0.002486918],"genre_scores_gemma":[0.8056412,0.000008513936,0.1942158,0.00003043445,0.000008137396,9.949985e-7,0.000008131849,0.000003130949,0.00008366445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9562852,"threshold_uncertainty_score":0.1932365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06305058343588359,"score_gpt":0.2937886414169703,"score_spread":0.2307380579810867,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}