{"id":"W4296912948","doi":"10.1109/tcss.2022.3204052","title":"Adaptive Collaboration With Training Plan Considering Role Correlation","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Social Systems","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"Natural Science Foundation of Chongqing; National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Process (computing); Plan (archaeology); Machine learning; Correlation; Knowledge management; Process management; 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":[0.002790972,0.0009155461,0.0009790275,0.0006730705,0.00104668,0.001286263,0.002066639,0.001622646,0.002658855],"category_scores_gemma":[0.008421586,0.0004173283,0.0008376217,0.0008319023,0.001055172,0.002585388,0.0024736,0.001667106,0.000316663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008949814,"about_ca_system_score_gemma":0.002479881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002980443,"about_ca_topic_score_gemma":0.002454279,"domain_scores_codex":[0.996758,0.001486351,0.0001643917,0.0006630379,0.0005557878,0.0003723735],"domain_scores_gemma":[0.9953034,0.002521206,0.0006353005,0.0005556059,0.0004511882,0.0005333282],"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":[0.0004650549,0.0005604729,0.004800725,0.0003213038,0.0001125513,0.0007201502,0.001121943,0.6824892,0.0065655,0.1420697,0.003806628,0.1569667],"study_design_scores_gemma":[0.00004352413,0.0001122992,0.0003688429,0.00001734552,0.00002363722,0.00017083,0.0001716076,0.9688038,0.001244068,0.02721895,0.001805789,0.00001924112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04314737,0.0001648758,0.9507865,0.0004267243,0.00004618031,0.0002258756,0.00005743177,0.0002472737,0.004897749],"genre_scores_gemma":[0.6786246,0.0001682273,0.3177174,0.0001209299,0.00004707163,0.0002999467,0.0001345881,0.00003958238,0.002847725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002980443,"threshold_uncertainty_score":0.01476026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03787212153739823,"score_gpt":0.2415006091697866,"score_spread":0.2036284876323884,"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."}}