{"id":"W4385508691","doi":"10.1002/iis2.12924","title":"Illustrating Business Relevance of Systems Engineering via Storytelling","year":2022,"lang":"en","type":"article","venue":"INCOSE International Symposium","topic":"Systems Engineering Methodologies and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Adaptability; Flexibility (engineering); Context (archaeology); Relevance (law); Computer science; Situational ethics; Value (mathematics); Storytelling; Knowledge management; Collaborative engineering; Engineering; Narrative; Management; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003336279,0.0001383516,0.0001834658,0.0001061764,0.00006929583,0.00002309822,0.0003802895,0.00003959538,0.00002870118],"category_scores_gemma":[0.00005577039,0.0001634948,0.00005149625,0.0002922844,0.00001329704,0.00009394606,0.0000916485,0.0001984344,0.000004852438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002427628,"about_ca_system_score_gemma":0.000011408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009284902,"about_ca_topic_score_gemma":0.00000139768,"domain_scores_codex":[0.998946,0.00001957624,0.000401143,0.000158382,0.0003068354,0.000168109],"domain_scores_gemma":[0.9993349,0.000235255,0.00008592897,0.0002095443,0.0001046572,0.00002965609],"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":[0.000002665951,0.00001252124,0.00009551401,0.00008068779,0.00004440235,0.000003742759,0.00008459785,0.8558927,0.1415525,0.001629132,0.0001193899,0.00048211],"study_design_scores_gemma":[0.0001647862,0.00001626555,0.0003131033,0.00006359806,0.000009946079,0.0000698072,0.0001594424,0.9526545,0.005801301,0.00003703034,0.04047581,0.0002343973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3696437,0.001124025,0.6176744,0.0001479689,0.007963909,0.0003631541,0.00009810265,0.000766036,0.002218671],"genre_scores_gemma":[0.9951804,0.00005107972,0.004086082,0.000005607129,0.0003085629,0.0002074261,0.00002369741,0.00004354641,0.00009355018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6255367,"threshold_uncertainty_score":0.6667124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01678609722885511,"score_gpt":0.2290090462858534,"score_spread":0.2122229490569983,"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."}}