{"id":"W4307237985","doi":"10.26443/glsars.v2i1.187","title":"Study of Legal Adaptation in China's Wind Power Development","year":2022,"lang":"en","type":"article","venue":"McGill GLSA Research Series","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Renewable energy; Wind power; China; Electricity; Electricity generation; Electricity market; Business; Energy development; Environmental economics; Energy law; Nameplate capacity; Economics; Market economy; Power (physics); Engineering; Law; Electrical engineering; Environmental law; 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":[0.001149889,0.00009497307,0.0001565939,0.0005023699,0.0002658538,0.00001952806,0.0002062845,0.0000253516,0.00009791776],"category_scores_gemma":[0.00006594669,0.0001056344,0.00001319925,0.001245739,0.0000191424,0.0002579256,0.0001454664,0.0003467154,0.000005300122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004519829,"about_ca_system_score_gemma":0.00006575151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002022602,"about_ca_topic_score_gemma":0.0005664189,"domain_scores_codex":[0.9981101,0.0002799399,0.0003202649,0.0001716514,0.0008005945,0.0003175184],"domain_scores_gemma":[0.9996112,0.00004497744,0.00002719901,0.0001893878,0.00008887005,0.00003835563],"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":[0.0001793751,0.0005823736,0.002523791,0.0001132854,0.00008498652,0.0001108956,0.02299201,0.9664248,0.001756606,0.001619459,0.0006280427,0.002984418],"study_design_scores_gemma":[0.01001272,0.01054624,0.3206755,0.0002419189,0.00002698678,0.0001540208,0.1903837,0.110743,0.03805218,0.0004485339,0.3163239,0.00239136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914268,0.0001014064,0.0001075169,0.00004000925,0.0001534016,0.0006430206,0.00000950051,0.00007786693,0.007440452],"genre_scores_gemma":[0.9988899,0.000006555064,0.0003469542,0.000001802435,0.000005839036,0.0001568638,0.00001087338,0.00002615126,0.0005550716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8556818,"threshold_uncertainty_score":0.4307646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03624894805522016,"score_gpt":0.2849902571366787,"score_spread":0.2487413090814586,"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."}}