{"id":"W2154952107","doi":"10.1002/rob.21409","title":"Field trial results of planetary rover visual motion estimation in Mars analogue terrain","year":2012,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Mars Exploration Program; Traverse; Terrain; Visual odometry; Inertial measurement unit; Computer science; Artificial intelligence; Odometry; Computer vision; Exploration of Mars; Simulation; Remote sensing; Robot; Mobile robot; Geodesy; Geography","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":[0.0003261582,0.00008396048,0.0001981033,0.0001752705,0.00001234126,0.00001033773,0.00006470161,0.0001449595,0.000008740871],"category_scores_gemma":[0.0002565898,0.00007753818,0.00006158113,0.0001145706,0.000006514791,0.0001809392,0.000007055008,0.0002242932,0.000001697377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003230486,"about_ca_system_score_gemma":0.00001335985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002905475,"about_ca_topic_score_gemma":0.00002308353,"domain_scores_codex":[0.9989918,0.00003850555,0.0006094619,0.00004261385,0.0001787576,0.0001388208],"domain_scores_gemma":[0.9994295,0.0002216252,0.0001694555,0.0000787489,0.0000444185,0.00005627289],"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":[0.001325168,0.00007649052,0.001197193,0.00003459413,0.00002205541,0.000006257059,0.0001933532,0.9901597,0.0001854325,0.00007590394,0.001707422,0.005016437],"study_design_scores_gemma":[0.007257856,0.0009762476,0.003157856,0.0001137979,0.00004564184,0.0000200186,0.00006662539,0.9846065,0.003392928,0.0001124987,0.0001147211,0.0001353298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2556973,0.0001378897,0.7416623,0.0004808712,0.001615015,0.0001276572,0.000004002248,0.0000249384,0.0002501169],"genre_scores_gemma":[0.9922209,0.00005769923,0.007344754,0.00007281914,0.0002661131,2.379208e-7,0.0000145916,0.00001381996,0.000009102162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7365236,"threshold_uncertainty_score":0.3161915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249572241575878,"score_gpt":0.2493904493179123,"score_spread":0.2368947269021535,"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."}}