{"id":"W4377832592","doi":"10.18280/ts.400245","title":"Damage Identification Method of Wind Turbine Generator System Blades Based on Image Processing Technology","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"People's Government of Jilin Province","keywords":"Identification (biology); Generator (circuit theory); Image processing; Computer science; Turbine blade; Turbine; Steam turbine; Image (mathematics); Artificial intelligence; Computer vision; Marine engineering; Engineering; Mechanical engineering; Power (physics); Physics; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008347085,0.0001625231,0.0002089888,0.0005109479,0.00008410097,0.00002878051,0.0001282165,0.00008340748,0.00005101045],"category_scores_gemma":[0.00003164924,0.0001599445,0.00005453619,0.000885502,0.00003407728,0.0001276414,0.00001136823,0.0001270858,0.00002416595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009077478,"about_ca_system_score_gemma":0.00001901268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.131351e-7,"about_ca_topic_score_gemma":5.461972e-7,"domain_scores_codex":[0.9987962,0.00007243671,0.000394275,0.0002200106,0.000304041,0.0002130053],"domain_scores_gemma":[0.9995145,0.00005150568,0.00009672095,0.000186572,0.0001068542,0.00004391086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001944418,0.00002016818,0.00005812639,0.0003502057,0.00001746378,0.000003837484,0.00004958063,0.1456933,0.8300189,0.0001375133,0.00009388404,0.0235375],"study_design_scores_gemma":[0.0003749265,0.00004843322,0.0005515944,0.00007560583,0.00002328995,0.000001122786,0.0001584781,0.4349447,0.5633675,0.00005101428,0.0002935536,0.0001096794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08122969,0.00005358466,0.9166046,0.00005418332,0.0001861129,0.0002936586,0.00001399027,0.001000806,0.0005633698],"genre_scores_gemma":[0.915015,0.000002650931,0.08471201,0.00001209998,0.0001028942,0.00005364818,0.00001800614,0.00003761952,0.00004602713],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8337854,"threshold_uncertainty_score":0.6522348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240131631630793,"score_gpt":0.2838403788745267,"score_spread":0.2614390625582187,"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."}}