{"id":"W2145392243","doi":"10.1109/robot.1996.506912","title":"Limited mobility grasps for fixtureless assembly","year":2002,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Position (finance); Object (grammar); Convergence (economics); Computer vision; Computer science; Robot end effector; Plane (geometry); Artificial intelligence; Motion (physics); Orientation (vector space); Sensitivity (control systems); Robot; Topology (electrical circuits); Algorithm; Mathematics; Geometry; 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":[0.0003385404,0.0004170217,0.0004841427,0.0004470316,0.0003649999,0.0004339803,0.0006869537,0.0005430406,0.001511173],"category_scores_gemma":[0.001493289,0.0003108878,0.000384871,0.0002495595,0.0008755599,0.0009968218,0.001091761,0.0004678863,0.0003621881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003564986,"about_ca_system_score_gemma":0.0001952058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004717206,"about_ca_topic_score_gemma":0.0004466578,"domain_scores_codex":[0.9996988,0.00005680877,0.0000167066,0.00004243693,0.0001605454,0.00002476101],"domain_scores_gemma":[0.9995498,0.0001878636,0.0000933554,0.0001027768,0.00003614609,0.00003010526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003899793,0.00006249324,0.0006427848,0.0004796232,0.00007990736,0.001300286,0.0007368527,0.1802542,0.4167668,0.09009112,0.001845925,0.3073501],"study_design_scores_gemma":[0.0001979543,0.0007829774,0.001771482,0.00008739014,0.00005601029,0.002600878,0.0001108661,0.7923495,0.1001698,0.07974391,0.02199551,0.0001336996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05847779,0.000961905,0.9376734,0.0001127911,0.00003095299,0.00003000238,0.00001666397,0.0005376427,0.002158815],"genre_scores_gemma":[0.7888297,0.00062165,0.2069471,0.00006372851,0.00002957064,0.00009408767,0.00004723298,0.0000945309,0.00327249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001511173,"threshold_uncertainty_score":0.005055428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160090391694621,"score_gpt":0.2311143430574568,"score_spread":0.1895134391405106,"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."}}