{"id":"W4248596645","doi":"10.1109/wsc.2007.4419836","title":"Agent-based simulation for collaborative cranes","year":2007,"lang":"en","type":"article","venue":"2007 Winter Simulation Conference","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Multi-agent system; Human–computer interaction; Artificial intelligence","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":[0.0008676821,0.0008992806,0.001173553,0.0005807506,0.001295917,0.001801402,0.001882288,0.002093925,0.007092952],"category_scores_gemma":[0.002445155,0.0007098893,0.0009667138,0.0005198251,0.001291614,0.001399218,0.001891705,0.00159231,0.0006646496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564147,"about_ca_system_score_gemma":0.001938649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01821687,"about_ca_topic_score_gemma":0.01140971,"domain_scores_codex":[0.9993448,0.0003395751,0.00003634924,0.00007011487,0.0001602529,0.0000489147],"domain_scores_gemma":[0.9987839,0.0007712966,0.00007505411,0.0001097215,0.000147268,0.000112853],"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":[0.00003002537,0.00002159747,0.0001803443,0.0000256878,0.00001905703,0.00006257516,0.00006145456,0.9753231,0.0003141333,0.02115584,0.0002920785,0.002514055],"study_design_scores_gemma":[0.00002415246,0.000007921887,0.00002348761,0.000005822229,0.000003541813,0.000007643395,0.00001169026,0.9926695,0.0001215875,0.005276307,0.001843863,0.000004641669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03726967,0.0005086554,0.9318392,0.0006177177,0.0001651468,0.0003252999,0.0002406849,0.001294907,0.02773877],"genre_scores_gemma":[0.7112478,0.0008413832,0.2744588,0.0001142549,0.00005646525,0.001094634,0.000361041,0.0002083716,0.01161721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01821687,"threshold_uncertainty_score":0.03622168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06817092962262722,"score_gpt":0.3370553703083626,"score_spread":0.2688844406857354,"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."}}