{"id":"W2101875266","doi":"10.1109/ical.2008.4636155","title":"Knowledge-based grasping of unknown objects in unstructured urban environments","year":2008,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"GRASP; Robot; Artificial intelligence; Computer science; Mobile robot; Fuzzy logic; Search and rescue; Robotics; Urban search and rescue; Human–computer interaction; Object (grammar); Automation; Engineering","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":[0.0003694367,0.0002949571,0.0003894732,0.0004341977,0.0005240921,0.0006623378,0.0004489372,0.0006532469,0.0008423602],"category_scores_gemma":[0.001699146,0.0002519089,0.0003063999,0.0002741876,0.0009777597,0.001162556,0.0007785892,0.0002019253,0.0001970685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004289457,"about_ca_system_score_gemma":0.0004749736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003732385,"about_ca_topic_score_gemma":0.003909359,"domain_scores_codex":[0.9998129,0.00003523107,0.00001190709,0.0000443079,0.00006520894,0.00003045086],"domain_scores_gemma":[0.9995615,0.0002379569,0.00006558834,0.00005163399,0.00004976126,0.0000335625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002848997,0.0001423856,0.003106084,0.0002180969,0.00006584328,0.001667067,0.0008171958,0.8201225,0.0447633,0.01219059,0.0008337949,0.1157881],"study_design_scores_gemma":[0.00002471606,0.0001219004,0.003652508,0.00002371672,0.00001658798,0.0002144337,0.0003660607,0.965679,0.007787833,0.02092692,0.001157833,0.00002858998],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4638595,0.0003933105,0.5262317,0.0002712144,0.0000249007,0.00005839492,0.00005186703,0.0003388422,0.008770318],"genre_scores_gemma":[0.9744101,0.0001974606,0.02395102,0.00002934959,0.000006963551,0.00001813284,0.00004532801,0.00001198257,0.001329671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003732385,"threshold_uncertainty_score":0.007421315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821287238289046,"score_gpt":0.2090923090958192,"score_spread":0.1908794367129287,"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."}}