{"id":"W3110341679","doi":"10.1109/ccece47787.2020.9255714","title":"Multimodality Weight and Score Fusion for SLAM","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Trajectory; Simultaneous localization and mapping; Artificial intelligence; Computer science; Convolutional neural network; Feature (linguistics); Fusion; Deep learning; Computer vision; Robot; Layer (electronics); Sensor fusion; Pattern recognition (psychology); Mobile robot","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":[0.001219707,0.001228633,0.0008475847,0.001080036,0.0003111502,0.0006789743,0.0009991366,0.0006627723,0.001870362],"category_scores_gemma":[0.003411623,0.0003063859,0.0006565912,0.001217574,0.0004616688,0.00149313,0.002030716,0.001196235,0.0006254832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000681575,"about_ca_system_score_gemma":0.0007246134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006389416,"about_ca_topic_score_gemma":0.007594152,"domain_scores_codex":[0.9992737,0.0001338245,0.00004153429,0.0001820181,0.0002543607,0.0001145106],"domain_scores_gemma":[0.9992167,0.0001404002,0.00008776232,0.0001749091,0.0003294672,0.00005069426],"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":[0.0004665306,0.0001681752,0.003116075,0.0001184957,0.0001907726,0.00007470521,0.0001179804,0.2660807,0.02194639,0.004706569,0.003298639,0.699715],"study_design_scores_gemma":[0.00001564761,0.0001286534,0.001903402,0.00001250028,0.0000357247,0.00003776149,0.00002767648,0.9818231,0.008953677,0.005453794,0.001585199,0.00002279147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05455362,0.0006603189,0.9406167,0.0002065381,0.00009449646,0.00004621986,0.0002803255,0.002131382,0.001410396],"genre_scores_gemma":[0.8431351,0.0002558939,0.1530392,0.0001081253,0.00007801353,0.00006275998,0.0007657688,0.0001469845,0.002408069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006389416,"threshold_uncertainty_score":0.01270443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326866017705633,"score_gpt":0.2039325026825306,"score_spread":0.1806638425054743,"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."}}