{"id":"W2915323812","doi":"10.3384/ecp18148265","title":"Deployment process for Modelica-based models","year":2019,"lang":"en","type":"article","venue":"Linköping electronic conference proceedings","topic":"Modeling and Simulation Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Maple Leaf Foods","funders":"","keywords":"Modelica; Computer science; Software deployment; Process (computing); Software engineering; Systems engineering; Programming language; Engineering","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":[0.003694662,0.002075608,0.001123791,0.002002409,0.001205703,0.00331092,0.002011491,0.001541806,0.02244652],"category_scores_gemma":[0.01596185,0.00208584,0.002162535,0.001153466,0.0009077655,0.003237951,0.004105342,0.003519625,0.010697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275747,"about_ca_system_score_gemma":0.001934143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005447381,"about_ca_topic_score_gemma":0.003455124,"domain_scores_codex":[0.997071,0.000978169,0.0001785296,0.000372465,0.001208166,0.0001916227],"domain_scores_gemma":[0.9938904,0.002720261,0.0001772839,0.001846921,0.00119965,0.0001655325],"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":[0.0003222727,0.0005221505,0.002348344,0.0009779455,0.0002539239,0.001700163,0.003735683,0.3580457,0.02095256,0.2384774,0.03472039,0.3379435],"study_design_scores_gemma":[0.000104502,0.000114859,0.0004174214,0.0003002502,0.00008024341,0.0003289568,0.0003199434,0.7060007,0.01530508,0.05086758,0.2260587,0.0001016779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003595549,0.0001307307,0.9694435,0.0003090607,0.0001147702,0.0002192769,0.0002316308,0.01299283,0.01296267],"genre_scores_gemma":[0.1182057,0.000995749,0.8473891,0.0002812437,0.0001179014,0.0008757525,0.00299176,0.009126442,0.02001636],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02244652,"threshold_uncertainty_score":0.07509106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04525528449737311,"score_gpt":0.2835251158017983,"score_spread":0.2382698313044252,"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."}}