{"id":"W1492019551","doi":"10.1007/978-3-540-77554-6_13","title":"Situated Decision Support Approach for Managing Multiple Negotiations","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Situated; Negotiation; Computer science; Offset (computer science); Decision support system; Knowledge management; Process (computing); Process management; Work (physics); Risk analysis (engineering); Control (management); Operations research; Artificial intelligence; Business; Engineering; Political science","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":[0.002218023,0.0007802035,0.0009291933,0.0009648366,0.001287093,0.00362575,0.003142987,0.002189074,0.01173733],"category_scores_gemma":[0.004552355,0.0005919235,0.0010367,0.001107031,0.001291942,0.003531001,0.003128393,0.002136175,0.001707928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000983925,"about_ca_system_score_gemma":0.001514851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002341666,"about_ca_topic_score_gemma":0.002663343,"domain_scores_codex":[0.9981349,0.0006580782,0.0001288233,0.0002507753,0.0006922273,0.0001351654],"domain_scores_gemma":[0.9982333,0.001092471,0.00006959631,0.0002480498,0.0002173175,0.0001391729],"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":[0.000395713,0.0003467726,0.000502446,0.0003557532,0.0001697245,0.0009956158,0.001800137,0.1204001,0.01076226,0.5897089,0.004938807,0.2696238],"study_design_scores_gemma":[0.0001103253,0.0001275368,0.000122901,0.00005531608,0.0001070677,0.0002798056,0.0003594531,0.6884481,0.006095422,0.2792197,0.02501951,0.00005478044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004032303,0.0001572306,0.9843181,0.0002021021,0.00006463766,0.00008735056,0.00003166115,0.0004764863,0.01063011],"genre_scores_gemma":[0.1994386,0.0002290351,0.7885857,0.00009788139,0.0000448979,0.0002229514,0.0001303683,0.00008540755,0.01116515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01173733,"threshold_uncertainty_score":0.03926522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02460342863091525,"score_gpt":0.241356644187052,"score_spread":0.2167532155561367,"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."}}