{"id":"W2184386128","doi":"","title":"Estimating and Correcting Bias in Stereo Visual Odometry","year":2014,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual odometry; Artificial intelligence; Computer vision; Odometry; Computer science; Robot; Mobile robot","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002117467,0.000526224,0.0006854878,0.001115803,0.0004459709,0.0008645242,0.0008545846,0.0007488361,0.0007311406],"category_scores_gemma":[0.0107055,0.000533858,0.0004705175,0.001232788,0.0005853421,0.001047159,0.001499941,0.0007708058,0.0003973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007901893,"about_ca_system_score_gemma":0.001185139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005413769,"about_ca_topic_score_gemma":0.004662557,"domain_scores_codex":[0.998359,0.000337664,0.00006680965,0.0002373678,0.0008868023,0.000112364],"domain_scores_gemma":[0.9969318,0.001178794,0.0004068637,0.0004596744,0.0009720557,0.00005080081],"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":[0.0001993319,0.00008013895,0.01553773,0.0003031144,0.0001434668,0.0001231035,0.0004356637,0.3351834,0.03793879,0.01639626,0.001938028,0.5917209],"study_design_scores_gemma":[0.00002267507,0.00008757487,0.006434882,0.00007166941,0.00003540036,0.0001719447,0.00007820115,0.9457804,0.03021744,0.01328147,0.003768444,0.00004991636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04658687,0.0004184791,0.9512533,0.00006499324,0.00005085809,0.00003030152,0.00005202425,0.0005375408,0.001005619],"genre_scores_gemma":[0.5174537,0.000549197,0.4801668,0.00007931961,0.00004473232,0.00007492497,0.0002110451,0.0002270484,0.001193255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005413769,"threshold_uncertainty_score":0.0111984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207435225380696,"score_gpt":0.304453584109012,"score_spread":0.2837100615709424,"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."}}