{"id":"W2119503754","doi":"10.1109/hicss.1995.375724","title":"Simulation and analysis of negotiation processes: the case of Softwood Lumber Negotiations","year":2002,"lang":"en","type":"article","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Negotiation; Flexibility (engineering); Computer science; Process (computing); Management science; Softwood; Cognition; Operations research; Software engineering; Artificial intelligence; Data science; Engineering; Sociology; Psychology; Mathematics; Programming language; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001617395,0.00004190594,0.00008889702,0.0001620138,0.00009316221,0.00003692584,0.0001288918,0.00001542747,0.0000444615],"category_scores_gemma":[0.000283984,0.0000291015,0.00003321241,0.002216707,0.00005098834,0.0005089463,0.00005732199,0.0000228059,0.000001467018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004670916,"about_ca_system_score_gemma":0.00001460408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009983735,"about_ca_topic_score_gemma":0.000290682,"domain_scores_codex":[0.9994944,0.00002687539,0.0001640744,0.0001393741,0.0001050088,0.00007026271],"domain_scores_gemma":[0.9989887,0.0004129176,0.000115289,0.0001685868,0.0002946309,0.00001984135],"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":[0.000004153361,0.0005242639,0.06936061,0.0001975519,0.0008449376,0.00002735345,0.05087357,0.4252814,0.00134396,0.08070473,0.0002381132,0.3705994],"study_design_scores_gemma":[0.0000606906,0.00001515261,0.009053082,0.00000384444,0.00009368495,0.000004691557,0.000288406,0.9897722,0.0001915201,0.0004595323,0.00001934675,0.00003782915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2049942,0.0000495676,0.7931656,0.0003032452,0.00001717399,0.00008194405,0.000002068647,0.00001695017,0.001369238],"genre_scores_gemma":[0.9972395,0.000007561869,0.002561038,0.00008371593,0.000005030365,0.000002539851,9.010986e-7,9.484335e-7,0.00009872701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7922454,"threshold_uncertainty_score":0.1186725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03464226035488059,"score_gpt":0.2824497323277848,"score_spread":0.2478074719729041,"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."}}