{"id":"W3048761334","doi":"10.3390/s21093091","title":"DOE-SLAM: Dynamic Object Enhanced Visual SLAM","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer vision; Artificial intelligence; Robustness (evolution); Simultaneous localization and mapping; Computer science; Object (grammar); Pose; Monocular; Exploit; Trajectory; Video tracking; Robot; 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":[0.0005323224,0.0008514443,0.0008904579,0.0006408102,0.0003484713,0.0006223423,0.00147673,0.0006584981,0.001690118],"category_scores_gemma":[0.001223989,0.000418643,0.0005115496,0.0007847022,0.0005242487,0.001126569,0.002217626,0.000822339,0.0009999716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003648032,"about_ca_system_score_gemma":0.0008327913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003515407,"about_ca_topic_score_gemma":0.005459526,"domain_scores_codex":[0.9994092,0.0001012203,0.00002434062,0.000154141,0.0002097155,0.0001014462],"domain_scores_gemma":[0.9996051,0.00008372395,0.0000476445,0.0001412631,0.00009396689,0.0000282437],"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":[0.0002427155,0.0001267783,0.001363316,0.0002531624,0.000136364,0.0002301641,0.0001798562,0.3063943,0.05139326,0.01146568,0.009125917,0.6190885],"study_design_scores_gemma":[0.00003292615,0.0001376157,0.0006315978,0.00001563869,0.00001635465,0.0001354918,0.00004594612,0.9727297,0.01105722,0.004956655,0.01021466,0.00002624763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005802235,0.0001867712,0.9909799,0.00004015123,0.00007316732,0.00002667814,0.00006219765,0.001840255,0.0009887094],"genre_scores_gemma":[0.4443486,0.0003794227,0.5490376,0.0002072391,0.0001026816,0.0001494478,0.0006067588,0.0003763716,0.004791992],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003515407,"threshold_uncertainty_score":0.006989837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004179687517758217,"score_gpt":0.2191375038064673,"score_spread":0.2149578162887091,"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."}}