{"id":"W1980367442","doi":"10.1016/j.dss.2014.06.009","title":"An experimental study of software agent negotiations with humans","year":2014,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Negotiation; Individualism; Software agent; Set (abstract data type); Computer science; Software; Product (mathematics); Process (computing); Knowledge management; Process management; Risk analysis (engineering); Business; Artificial intelligence; Political science; Law; 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":[0.006102598,0.0007214115,0.0007567234,0.0005710666,0.001838732,0.001949076,0.002003494,0.001982248,0.01348321],"category_scores_gemma":[0.05981899,0.0005552851,0.0003741502,0.0007827549,0.002271072,0.003025118,0.001599272,0.002123055,0.001249053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006341451,"about_ca_system_score_gemma":0.0007156418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001046963,"about_ca_topic_score_gemma":0.0006895288,"domain_scores_codex":[0.9939593,0.004328947,0.0002817414,0.0005108245,0.0006849755,0.000234118],"domain_scores_gemma":[0.8822453,0.1048591,0.003778683,0.005495823,0.001975958,0.001645076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.08032455,0.1949825,0.07173867,0.006033619,0.001352083,0.00424873,0.08092068,0.03988432,0.1198808,0.1396124,0.01694311,0.2440785],"study_design_scores_gemma":[0.02587701,0.1945398,0.1260998,0.001221057,0.001383429,0.006349246,0.05802194,0.2261168,0.1090838,0.1713455,0.0790388,0.0009227413],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818927,0.0002415929,0.005088296,0.0003463345,0.0001056332,0.0003136619,0.0001520585,0.00006078456,0.01179898],"genre_scores_gemma":[0.988891,0.0001832539,0.005581085,0.0001653117,0.00007651422,0.000456962,0.0002516254,0.00004567901,0.004348564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01348321,"threshold_uncertainty_score":0.04510581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383335041847852,"score_gpt":0.3051997118098388,"score_spread":0.2713663613913603,"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."}}