{"id":"W2774992637","doi":"10.4018/978-1-59140-562-7.ch048","title":"Improving Dynamic Decision Making through HCI Principles","year":2006,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Dynamic decision-making; Computer science; Management science; Space (punctuation); Business decision mapping; Control (management); Empirical research; Knowledge management; Operations research; Decision support system; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001915598,0.001082219,0.001694352,0.0004427329,0.0006151638,0.00175847,0.002653888,0.0009002105,0.0004370282],"category_scores_gemma":[0.001190577,0.0008595696,0.001099071,0.0001746021,0.0002257703,0.0003017533,0.00187856,0.0006543016,0.002088335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000808769,"about_ca_system_score_gemma":0.0004336546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001911468,"about_ca_topic_score_gemma":0.001339901,"domain_scores_codex":[0.9883158,0.0001053353,0.003268182,0.002332354,0.005077156,0.0009011332],"domain_scores_gemma":[0.9918962,0.001901255,0.002278457,0.002880048,0.0008275704,0.0002164646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007274922,0.000009771305,0.00004609803,0.00001478773,0.00003122154,0.0002143494,0.00004046867,0.0003197826,0.00001507358,0.8563912,0.01599973,0.1268448],"study_design_scores_gemma":[0.0003333585,0.00005929029,0.0002304209,0.0007166397,0.00004174726,0.000177533,0.00003549006,0.003713045,0.0000016781,0.7589322,0.2350232,0.0007353332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0004353538,0.002650927,0.1304687,0.00001846231,0.002347027,0.0006649942,0.0002444758,0.0002552924,0.8629147],"genre_scores_gemma":[0.6538675,0.000001884437,0.02083001,0.0004198222,0.0007703158,0.00002050196,0.000003182369,0.0001558522,0.3239309],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6534322,"threshold_uncertainty_score":0.9993855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08972849876374143,"score_gpt":0.3648326403186637,"score_spread":0.2751041415549222,"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."}}