{"id":"W4391277777","doi":"10.1016/j.ins.2024.120231","title":"Probabilistic rotation modeling based on directional mixture density networks","year":2024,"lang":"en","type":"article","venue":"Information Sciences","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Robustness (evolution); Probabilistic logic; Artificial intelligence; Algorithm; Ambiguity; Statistical model; Noise (video); Machine learning; Flexibility (engineering); Rotation (mathematics); Pattern recognition (psychology); Mathematics; Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001206539,0.0009075757,0.001343173,0.001258402,0.0004958901,0.001190527,0.001767461,0.001077528,0.002260898],"category_scores_gemma":[0.004754448,0.001200876,0.001475346,0.002015381,0.001078926,0.001956175,0.001317378,0.001513005,0.001169603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008066961,"about_ca_system_score_gemma":0.0007815619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030338,"about_ca_topic_score_gemma":0.009605645,"domain_scores_codex":[0.999149,0.0003138187,0.00003906187,0.0002169443,0.0002011436,0.0000800174],"domain_scores_gemma":[0.998485,0.0008990418,0.0001839101,0.0001630676,0.0002155452,0.00005342384],"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":[0.00008919344,0.00001895314,0.0006528108,0.00004128471,0.00005474471,0.00003118355,0.00004925513,0.9485742,0.0009626563,0.01886667,0.0005739836,0.03008491],"study_design_scores_gemma":[0.000002691709,0.000006407369,0.00009990212,0.000003375261,0.000008414411,0.00001403758,0.000002934618,0.9954788,0.000178221,0.003901623,0.0002971426,0.000006450243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004325774,0.000166878,0.9945828,0.00007307001,0.00003210615,0.00001248664,0.00005557564,0.0002079414,0.0005433431],"genre_scores_gemma":[0.7250661,0.001877894,0.2613063,0.0001623384,0.0001902235,0.000229857,0.001044184,0.0003553217,0.009767763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01030338,"threshold_uncertainty_score":0.02048683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358985628736225,"score_gpt":0.2236033816651304,"score_spread":0.2100135253777682,"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."}}