{"id":"W2157492811","doi":"10.1109/robot.2006.1641959","title":"An approach for object manipulation using cooperative agents","year":2006,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Fence (mathematics); Computer science; Flexibility (engineering); Object (grammar); Point (geometry); Orientation (vector space); Human–computer interaction; Task (project management); Computer vision; Position (finance); Artificial intelligence; Simulation; Engineering; Mathematics","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":[0.0003033859,0.0005408177,0.0003864077,0.0003525517,0.0005661997,0.0006221104,0.001384681,0.001064241,0.00195252],"category_scores_gemma":[0.0005483726,0.0002832767,0.0006499862,0.0002873602,0.001157409,0.0008556084,0.00112489,0.0007913327,0.0003393434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005231842,"about_ca_system_score_gemma":0.0007040557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001351546,"about_ca_topic_score_gemma":0.000965164,"domain_scores_codex":[0.9997329,0.00006073686,0.000009847397,0.00005894605,0.0001166337,0.00002081551],"domain_scores_gemma":[0.9998418,0.00006685186,0.00002227101,0.00002561065,0.00002724519,0.00001607526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006307232,0.00009306012,0.0003723175,0.0002659141,0.00007591891,0.0004120617,0.0006017192,0.4097585,0.03862146,0.4516075,0.00200946,0.09611896],"study_design_scores_gemma":[0.0000429018,0.0001354725,0.0001001723,0.00002354361,0.0000229742,0.0001606365,0.00005867147,0.9015056,0.004072211,0.07388965,0.01996555,0.00002255268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003586931,0.0001811069,0.9921307,0.0001561439,0.00002736497,0.000028583,0.000005915387,0.000103201,0.003779998],"genre_scores_gemma":[0.3941932,0.0008005055,0.594666,0.0001859016,0.00009209188,0.0004258018,0.0000409403,0.0000483924,0.009547163],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00195252,"threshold_uncertainty_score":0.006531835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05770699735729338,"score_gpt":0.2843171340980024,"score_spread":0.226610136740709,"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."}}