{"id":"W2566144850","doi":"","title":"Argumentation in Multi-Agent Systems. 7th International Workshop, ArgMAS 2010, Toronto Canada","year":2011,"lang":"en","type":"article","venue":"Springer US","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Argumentation theory; Computer science; Operations research; Engineering; Epistemology; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002610987,0.0001371279,0.0001398785,0.00006620708,0.00005118121,0.00009534399,0.0005357909,0.00005437029,0.0001006031],"category_scores_gemma":[0.00001999662,0.0001347837,0.00003295532,0.00009350619,0.000007638774,0.0006099092,0.0001201976,0.00007877659,0.00004065458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007834825,"about_ca_system_score_gemma":0.0001244497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7086803,"about_ca_topic_score_gemma":0.7257362,"domain_scores_codex":[0.9986172,0.00006081664,0.0003668297,0.0003419934,0.0003699473,0.0002431657],"domain_scores_gemma":[0.9993104,0.00002155791,0.0001634836,0.000349366,0.00006496192,0.00009019954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008409234,0.001256315,0.8763148,0.0002859314,0.000388713,0.0004321026,0.02646583,0.006385616,0.0067306,0.03512247,0.02061497,0.02591858],"study_design_scores_gemma":[0.001087034,0.00001947412,0.8442745,0.0001310303,0.000006488821,0.000009594833,0.0004830401,0.1412389,0.001624578,0.00001348215,0.01072728,0.0003846192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4514246,0.001213205,0.5132293,0.000337517,0.02592757,0.001102587,0.00001296362,0.0002141449,0.006538171],"genre_scores_gemma":[0.9925721,0.0000210701,0.00573844,0.0001044132,0.00009186269,0.00004845904,0.000006201513,0.00001009281,0.001407339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5411475,"threshold_uncertainty_score":0.5496318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05391690132820052,"score_gpt":0.2560538017673451,"score_spread":0.2021369004391446,"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."}}