{"id":"W4213014928","doi":"10.33448/rsd-v11i3.26408","title":"Hydropower projects and environmental licensing process: how different countries manages the problem","year":2022,"lang":"en","type":"article","venue":"Research Society and Development","topic":"Hydropower, Displacement, Environmental Impact","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydroelectricity; License; Hydropower; Indigenous; Bureaucracy; Process (computing); Bottleneck; Environmental impact assessment; Business; Order (exchange); Environmental planning; Developing country; Political science; Engineering; Geography; Economic growth; Operations management; Economics; Computer science; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005911727,0.0001648342,0.0002988367,0.002098484,0.002003997,0.006275461,0.0008633375,0.0009389669,0.004113049],"category_scores_gemma":[0.01794867,0.0001854318,0.0003693633,0.002905102,0.002976642,0.004766069,0.003551977,0.000818401,0.0002442291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003458421,"about_ca_system_score_gemma":0.004789318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01719108,"about_ca_topic_score_gemma":0.01601518,"domain_scores_codex":[0.994263,0.002513919,0.000399713,0.0005231473,0.001205864,0.001094426],"domain_scores_gemma":[0.9893199,0.005544809,0.002021415,0.000606737,0.001790797,0.0007163482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001285534,0.0003278222,0.3124037,0.0008076081,0.0002226001,0.001606215,0.0393482,0.0105356,0.001795818,0.4099868,0.003506834,0.2193304],"study_design_scores_gemma":[0.00007947814,0.0002888262,0.4847466,0.001717434,0.0002423864,0.001705289,0.2121657,0.0119306,0.003205266,0.1008726,0.1828274,0.0002183075],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8608366,0.002350509,0.007596652,0.0044684,0.00004535856,0.0001464148,0.0001126518,0.00003874805,0.1244046],"genre_scores_gemma":[0.9976592,0.0003102367,0.0004324921,0.00007790692,0.000005205276,0.00001021028,0.00001481728,0.000006669324,0.001483151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01719108,"threshold_uncertainty_score":0.03418201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04323251272635282,"score_gpt":0.3984403874456052,"score_spread":0.3552078747192524,"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."}}