{"id":"W2218781582","doi":"","title":"A Simulation-Based Innovation Forecasting Approach Combining the Bass Diffusion Model, the Discrete Choice Model and System Dynamics An Application in the German Market for Electric Cars","year":2011,"lang":"en","type":"article","venue":"","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"German; Discrete choice; Bass (fish); Innovation diffusion; Computer science; System dynamics; Electric cars; Diffusion; Econometrics; Industrial engineering; Economics; Engineering; Artificial intelligence; Machine learning; Electrical engineering; Physics","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":[0.001263077,0.0005930527,0.001240266,0.0008440622,0.0005975509,0.001165968,0.0008184349,0.001428772,0.002276597],"category_scores_gemma":[0.003667428,0.0004166956,0.0009536785,0.000846283,0.0004206326,0.001151943,0.0005540956,0.0008991182,0.0002275526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000934699,"about_ca_system_score_gemma":0.001279262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01765565,"about_ca_topic_score_gemma":0.008416781,"domain_scores_codex":[0.9996099,0.0002179747,0.00002145946,0.0000506793,0.00007209056,0.00002794307],"domain_scores_gemma":[0.9979013,0.001664524,0.00008106227,0.00006787814,0.0002040268,0.00008128615],"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":[0.00006531874,0.00007989994,0.001210101,0.00003936109,0.00006763988,0.00006589838,0.00003963989,0.9731593,0.0009604067,0.01113227,0.0001881432,0.01299205],"study_design_scores_gemma":[0.000005371875,0.00001072265,0.00008919488,0.000001826039,0.00000627278,0.000006412055,0.000002859347,0.9983859,0.0001000508,0.001300625,0.00008609725,0.000004676794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1526452,0.000374618,0.8412985,0.0006114377,0.0001253097,0.00008509694,0.000132713,0.0004036563,0.004323436],"genre_scores_gemma":[0.9340054,0.0002910562,0.06364736,0.00003967353,0.00004199297,0.0001091438,0.000146774,0.00002913049,0.001689463],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01765565,"threshold_uncertainty_score":0.03510576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1425553039969645,"score_gpt":0.3467952345396423,"score_spread":0.2042399305426779,"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."}}