{"id":"W3157983709","doi":"10.1016/j.enconman.2021.114112","title":"A review of sensitivity analysis practices in wind resource assessment","year":2021,"lang":"en","type":"review","venue":"Energy Conversion and Management","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Centre Eau Terre Environnement, Institut National de la Recherche Scientifique; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Sensitivity (control systems); Wind power; Resource (disambiguation); Wind resource assessment; Computer science; Operations research; Environmental science; Engineering; Offshore wind power","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004417709,0.001862193,0.002229931,0.006027929,0.000351011,0.001722972,0.001573971,0.00156005,0.003759122],"category_scores_gemma":[0.01124225,0.0007740478,0.001453464,0.009035205,0.000720508,0.002274296,0.001117572,0.001579383,0.000961982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115812,"about_ca_system_score_gemma":0.00289425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00405567,"about_ca_topic_score_gemma":0.006189355,"domain_scores_codex":[0.9982764,0.0005026984,0.0003594975,0.0002272578,0.0005864527,0.00004775473],"domain_scores_gemma":[0.9891824,0.008685334,0.0006834189,0.0002172768,0.001145436,0.00008602134],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004875252,0.00007444612,0.0002473813,0.0715073,0.0003997674,0.0001026468,0.00007708449,0.004003933,0.001134121,0.00686194,0.01458262,0.9009599],"study_design_scores_gemma":[0.00003998945,0.0002633732,0.0029159,0.08360611,0.001780435,0.0008140801,0.0001722559,0.002291532,0.001949919,0.01882425,0.887183,0.0001591081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001162699,0.9966006,0.001823395,0.000304737,0.0001611163,0.00001383784,0.00007839777,0.00001398179,0.0008877809],"genre_scores_gemma":[0.001042633,0.9965327,0.001793026,0.000211572,0.0001388908,0.0000160393,0.00006730592,0.000006089435,0.0001918073],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9955823,"threshold_uncertainty_score":0.02336335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162880500878268,"score_gpt":0.3246172074918345,"score_spread":0.2929884024830518,"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."}}