{"id":"W4390268864","doi":"10.5383/ijtee.19.02.004","title":"Assessment of Wind Speed and Power Density Using Weibull and Rayleigh Distributions at Turbat, Balochistan, Pakistan","year":2021,"lang":"en","type":"article","venue":"International Journal of Thermal and Environmental Engineering","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Wind speed; Wind power; Environmental science; Meteorology; Rayleigh distribution; Renewable energy; Statistics; Mathematics; Engineering; Geography; Probability density function; Electrical engineering","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":[0.0003977898,0.0003977049,0.0002139932,0.001013414,0.000537264,0.0006627028,0.0003145903,0.0003402684,0.000390954],"category_scores_gemma":[0.0007682428,0.0002019767,0.000264022,0.001136253,0.0002521257,0.0004338217,0.0002514537,0.000256088,0.0001846738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004885701,"about_ca_system_score_gemma":0.000518759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0402888,"about_ca_topic_score_gemma":0.04584333,"domain_scores_codex":[0.9997258,0.00003792417,0.00002192525,0.00006505413,0.00009367168,0.00005562814],"domain_scores_gemma":[0.9995279,0.0001318832,0.00008287861,0.00003718351,0.0001890071,0.00003106532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001532655,0.00008510698,0.8877199,0.00006187202,0.00009861893,0.001313988,0.0005080684,0.06762626,0.005285332,0.0004104498,0.00106708,0.03567004],"study_design_scores_gemma":[0.00001333544,0.0001083566,0.8314205,0.00002782302,0.00003410788,0.0004160318,0.001657145,0.1622257,0.00251507,0.0002872606,0.001241303,0.00005343852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947001,0.00007315262,0.003267196,0.00004127029,0.000007170224,0.00001667989,0.0005034914,0.00004747681,0.001343611],"genre_scores_gemma":[0.9982712,0.0000604756,0.000958581,0.000005627478,0.000003648812,0.00001022304,0.0004423222,0.000004550348,0.0002432416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0402888,"threshold_uncertainty_score":0.08010858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005323409319347341,"score_gpt":0.217264513838537,"score_spread":0.2119411045191897,"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."}}