{"id":"W1516079915","doi":"10.1609/aaai.v24i1.7774","title":"Team Formation with Heterogeneous Agents in Computer Games","year":2010,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Task (project management); Computer science; Human–computer interaction; Engineering; Systems 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000353024,0.0001695775,0.0001886754,0.0001468518,0.000101431,0.0002164194,0.001095745,0.00007938607,0.00002718093],"category_scores_gemma":[0.00005116914,0.0001147694,0.00005627884,0.0003993271,0.0000910899,0.0006168215,0.0001686497,0.000263165,0.00005491188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000299222,"about_ca_system_score_gemma":0.00003922417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006172938,"about_ca_topic_score_gemma":0.0001396064,"domain_scores_codex":[0.9985372,0.00001439576,0.0004534157,0.0003412829,0.0004039088,0.0002498007],"domain_scores_gemma":[0.9989896,0.00003477648,0.0003508489,0.0002577685,0.0003067827,0.00006024664],"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":[0.0001317347,0.0006236679,0.007305617,0.0001738501,0.00002800765,0.000002813165,0.00878818,0.001719736,0.1212185,0.5988208,0.0003966203,0.2607904],"study_design_scores_gemma":[0.00005829436,0.0001858082,0.002337537,0.0001940165,0.000004005272,0.00001858556,0.00008577973,0.567189,0.4208396,0.008776344,0.0001120218,0.0001989751],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8960752,0.000003556577,0.100083,0.0008373848,0.0005672851,0.0005328908,0.000001703101,0.00006542404,0.001833556],"genre_scores_gemma":[0.9945309,0.000006019817,0.005189115,0.0001291721,0.00006439677,0.00002478875,5.024345e-7,0.000007815729,0.00004727115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5900444,"threshold_uncertainty_score":0.4680162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06497554769171661,"score_gpt":0.285766376035646,"score_spread":0.2207908283439294,"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."}}