{"id":"W2166646444","doi":"10.1109/robio.2007.4522409","title":"Building probabilistic motion models for SLAM","year":2007,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Odometry; Computer science; Artificial intelligence; Robot; Motion (physics); Probabilistic logic; Computer vision; Mobile robot; Ground truth; Component (thermodynamics); Recursive least squares filter; Algorithm","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":[0.0001363536,0.00006094612,0.00005804754,0.00004695199,0.00002908634,0.00001648528,0.00003230108,0.00004443979,0.000007675834],"category_scores_gemma":[0.00001941598,0.0000588629,0.00002611804,0.00007179977,0.000005519775,0.00006806611,0.000003124186,0.00002711454,0.000002958815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004399729,"about_ca_system_score_gemma":0.000002581341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000396645,"about_ca_topic_score_gemma":0.00001039409,"domain_scores_codex":[0.9995844,0.000002002587,0.0001275174,0.00007797415,0.00005876164,0.000149352],"domain_scores_gemma":[0.9998001,0.0000395407,0.000007983526,0.00007633337,0.00004253969,0.0000335285],"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":[0.000001978008,0.000005301388,0.000004976778,0.00003561903,0.000003323577,2.281075e-7,0.00001715427,0.8580769,0.00165466,0.1352689,0.0001155033,0.004815397],"study_design_scores_gemma":[0.0001252527,0.00001175315,0.00003402528,0.000006398674,0.000005680778,6.63419e-7,0.000007705993,0.9739891,0.00435852,0.02113133,0.0002521251,0.00007746051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01690652,0.00001680403,0.9781075,0.00001692974,0.0001632334,0.0002017208,0.000001175901,0.0002274395,0.00435868],"genre_scores_gemma":[0.9237216,0.000002420059,0.07606471,0.00002143892,0.00006617706,0.000005401707,0.000008576466,0.00001942512,0.00009031536],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.906815,"threshold_uncertainty_score":0.240036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951504205366896,"score_gpt":0.2356062228131716,"score_spread":0.2160911807595027,"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."}}