{"id":"W2112686536","doi":"10.5539/eer.v1n1p175","title":"Innovation and Technology Management in Wind Energy Cluster","year":2011,"lang":"en","type":"article","venue":"Energy and Environment Research","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão; Universidade de Aveiro","keywords":"Wind power; Incentive; Energy security; Environmental economics; Cluster (spacecraft); Field (mathematics); Computer science; Value (mathematics); Energy management; Industrial organization; Business; Power (physics); Energy (signal processing); Risk analysis (engineering); Renewable energy; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001082213,0.0001574672,0.0002551808,0.00150563,0.0006753381,0.002090029,0.0003640694,0.0009057158,0.001858024],"category_scores_gemma":[0.002787136,0.0001047749,0.0002450109,0.001491684,0.0007029863,0.001606745,0.0006955121,0.0003001018,0.0001695512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002632901,"about_ca_system_score_gemma":0.001393928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006659938,"about_ca_topic_score_gemma":0.005112177,"domain_scores_codex":[0.9994423,0.0001738076,0.00002757768,0.00008214282,0.0001150812,0.0001591849],"domain_scores_gemma":[0.9988397,0.0005338344,0.0002621149,0.00004402337,0.0001734588,0.0001468853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002525024,0.0004455459,0.07625394,0.0001698002,0.0001017073,0.0008926931,0.001711898,0.420112,0.004194799,0.3379545,0.003027349,0.1548833],"study_design_scores_gemma":[0.00004637863,0.0002945806,0.03866841,0.00006994882,0.00004949118,0.00015532,0.003228143,0.7887603,0.003250342,0.1552174,0.01019793,0.00006180743],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.931579,0.0007869546,0.03187132,0.001550365,0.00002455895,0.0001415536,0.00007025343,0.00003616806,0.03393983],"genre_scores_gemma":[0.9951389,0.0002575282,0.001843303,0.00001519449,0.000008126529,0.0000201461,0.00001693174,0.000001945728,0.002697854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006659938,"threshold_uncertainty_score":0.01910311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1558746193737564,"score_gpt":0.3566615402209807,"score_spread":0.2007869208472242,"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."}}