{"id":"W2897626350","doi":"10.3390/app8102004","title":"Condition Monitoring of Wind Turbine Blades Using Active and Passive Thermography","year":2018,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Thermography; Turbine blade; Thermal; Visibility; Acoustics; Turbine; Materials science; Nondestructive testing; Remote sensing; Marine engineering; Engineering; Mechanical engineering; Geology; Optics; Meteorology; Infrared","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003322275,0.0004243153,0.000407634,0.0008310621,0.0001701353,0.0004172445,0.000408905,0.0005462465,0.0008498981],"category_scores_gemma":[0.0006133146,0.0003305451,0.0001962541,0.0005207324,0.0003278317,0.0006540917,0.0002121985,0.0003005355,0.0002408731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649272,"about_ca_system_score_gemma":0.0001329762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004097057,"about_ca_topic_score_gemma":0.0007087935,"domain_scores_codex":[0.9997186,0.0000374601,0.00001554071,0.00008493292,0.0001252136,0.00001818967],"domain_scores_gemma":[0.9995854,0.000106801,0.0000831379,0.00005307446,0.000148225,0.00002321397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002122373,0.00005372503,0.004064858,0.0001712778,0.00001296441,0.0001211286,0.0001210692,0.001410286,0.9583554,0.0001608768,0.0001861099,0.03513018],"study_design_scores_gemma":[0.00004075876,0.0008327496,0.07183325,0.00004139189,0.00008017044,0.0008872304,0.0002452743,0.0648542,0.8584793,0.0003575328,0.002277496,0.00007076596],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261754,0.001367581,0.168793,0.00008127261,0.00007482822,0.0001105313,0.0002997566,0.0008055751,0.002292091],"genre_scores_gemma":[0.9498466,0.0005071703,0.04809609,0.00004079694,0.00002578388,0.00004387203,0.0001077708,0.00004011675,0.001291832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008498981,"threshold_uncertainty_score":0.002843201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542721381567646,"score_gpt":0.2516860113197,"score_spread":0.2362587975040236,"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."}}