{"id":"W4313001420","doi":"10.1109/iros47612.2022.9981588","title":"Behaviour Learning with Adaptive Motif Discovery and Interacting Multiple Model","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Interpretability; Motif (music); Computer science; Artificial intelligence; Estimator; Machine learning; Entropy (arrow of time); Gaussian; Mathematics; Statistics","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":[0.0002553594,0.000260561,0.000278835,0.0002033934,0.0003472853,0.0001556255,0.0002556096,0.00008449753,0.0001007378],"category_scores_gemma":[0.00002145861,0.0002420548,0.00004585857,0.0000875863,0.00008425448,0.0002683349,0.0001629107,0.0008823901,0.000007804117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002091706,"about_ca_system_score_gemma":0.00003303428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001453935,"about_ca_topic_score_gemma":0.00004966857,"domain_scores_codex":[0.998569,0.00006726777,0.000366864,0.0004018948,0.0003386813,0.000256332],"domain_scores_gemma":[0.9994568,0.0001060324,0.0001350401,0.0001576364,0.00006849971,0.00007602794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000132888,0.00005553513,0.01273193,0.00002619561,0.0001532347,0.00003473485,0.001139435,0.9566679,0.001955603,0.02445562,0.00009262044,0.002554308],"study_design_scores_gemma":[0.0002881073,0.0002358355,0.0006729065,0.0001043021,0.00001939543,0.00009489124,0.004542547,0.9928048,0.0006014928,0.0001425774,0.0002068483,0.0002862973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8852234,0.0002545448,0.1091293,0.0001439386,0.001049898,0.0003657029,0.00009417789,0.0002809318,0.003458082],"genre_scores_gemma":[0.9968245,0.0002009787,0.0001378109,0.00002763132,0.00005224815,0.0001623935,0.00003649192,0.00003867161,0.002519279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1116011,"threshold_uncertainty_score":0.9870708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03427360411468759,"score_gpt":0.240893922422245,"score_spread":0.2066203183075574,"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."}}