{"id":"W1545081442","doi":"","title":"A Metropolitan Wind Resource Assessment for Bangkok, Thailand Part 2: GIS Analysis and Technical Wind Resource Potential","year":2013,"lang":"en","type":"article","venue":"Journal of Sustainable Energy and Environment","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wind power; Metropolitan area; Turbine; Resource (disambiguation); Environmental science; Electricity; Work (physics); Meteorology; Wind speed; Quarter (Canadian coin); Electricity generation; Geography; Environmental engineering; Engineering; Power (physics); Computer science","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":[0.0003144685,0.0008347983,0.0002480884,0.003111145,0.0005804031,0.001539613,0.0002486887,0.0002158263,0.002167835],"category_scores_gemma":[0.0004710251,0.0004406086,0.0004673131,0.00517298,0.0001966448,0.0008198348,0.0006648261,0.0002557261,0.000406619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00280051,"about_ca_system_score_gemma":0.002326717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1805092,"about_ca_topic_score_gemma":0.1896034,"domain_scores_codex":[0.9997597,0.00006005669,0.00002696925,0.00003247472,0.00008958189,0.00003114057],"domain_scores_gemma":[0.9996679,0.00004866405,0.000048773,0.00001942059,0.0001703661,0.00004489303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005980168,0.0001770868,0.5129234,0.00156469,0.0005886499,0.003123033,0.002892376,0.2289538,0.0159762,0.005675806,0.01636152,0.2111655],"study_design_scores_gemma":[0.00005327242,0.0002186283,0.7938213,0.0003056188,0.0002911133,0.0007679533,0.0096334,0.1402503,0.008583872,0.001796389,0.04413018,0.0001479579],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956429,0.001607218,0.01554809,0.0003769294,0.00002987186,0.0006209633,0.04422116,0.0004219798,0.04153093],"genre_scores_gemma":[0.9497017,0.001242635,0.01814768,0.00003333461,0.000009438636,0.000412248,0.01984489,0.00007763178,0.01053037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1805092,"threshold_uncertainty_score":0.3589169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004286937940561186,"score_gpt":0.1983783166408924,"score_spread":0.1940913787003312,"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."}}