{"id":"W4401416175","doi":"10.1109/icra57147.2024.10611172","title":"DRIVE: Data-driven Robot Input Vector Exploration","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robot; Artificial intelligence; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002805749,0.0001251734,0.000147421,0.0001216453,0.00006750608,0.0005434635,0.001428497,0.00005007794,0.00002890142],"category_scores_gemma":[0.0000552666,0.0001010234,0.00003250731,0.0004559539,0.00002183022,0.002305263,0.0004503256,0.0001428762,0.001197994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003800324,"about_ca_system_score_gemma":0.0001141246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000215837,"about_ca_topic_score_gemma":0.000002824001,"domain_scores_codex":[0.9986222,0.0000549266,0.0002056796,0.0005917677,0.0003034218,0.0002219439],"domain_scores_gemma":[0.998598,0.000124388,0.00002815319,0.001131188,0.00003667812,0.00008154802],"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":[0.000007406234,0.0001668774,0.0003186072,0.0001473763,0.0002696585,0.001113121,0.007254229,0.126258,0.004805744,0.284222,0.254046,0.3213909],"study_design_scores_gemma":[0.00007828775,0.00002878242,0.0003007989,0.00004245455,0.00000690194,0.00002179229,0.0000168734,0.992095,0.0002903992,0.0007901004,0.006186564,0.0001420804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000810184,0.0001813492,0.989959,0.003736455,0.001822493,0.0001247936,0.000005664825,0.001084852,0.003004401],"genre_scores_gemma":[0.08391327,0.0000162266,0.9126792,0.0003216123,0.0003855624,0.00002063792,0.00008253082,0.0000178312,0.00256314],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8658369,"threshold_uncertainty_score":0.9995797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07456092153301755,"score_gpt":0.3144977725010019,"score_spread":0.2399368509679843,"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."}}