{"id":"W4380362645","doi":"10.1117/12.2665495","title":"Inspection of a helicopter blade using drone-based active thermography","year":2023,"lang":"en","type":"article","venue":"","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; National Research Council Canada","funders":"","keywords":"Drone; Blade (archaeology); Thermography; Aeronautics; Computer science; Aerospace engineering; Artificial intelligence; Engineering; Computer vision; Structural engineering; Physics; Optics; 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":[0.000170789,0.000284032,0.0002944073,0.0004035929,0.0002304683,0.00028503,0.0003642231,0.0004114892,0.001124411],"category_scores_gemma":[0.0003479795,0.0002078003,0.0001747817,0.0001430696,0.000275193,0.0003151273,0.0002720851,0.0001881485,0.0003016289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001582602,"about_ca_system_score_gemma":0.000176438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328536,"about_ca_topic_score_gemma":0.00313804,"domain_scores_codex":[0.9998533,0.00001580272,0.000006402157,0.00004616997,0.00006254945,0.00001578404],"domain_scores_gemma":[0.9997196,0.00006899342,0.00004901557,0.0000422529,0.00009465803,0.0000255638],"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":[0.0001709736,0.00006950245,0.002431636,0.0001821222,0.00001073762,0.00023673,0.0002287662,0.00146144,0.9717336,0.00008093532,0.0001894983,0.02320403],"study_design_scores_gemma":[0.00005651,0.002512951,0.04701502,0.00007810743,0.0000599686,0.001522267,0.0005388277,0.04915467,0.8939209,0.0001230827,0.00494227,0.00007546377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599918,0.0003647889,0.0371856,0.00005222501,0.00002955348,0.000118613,0.0001388045,0.0004411028,0.00167763],"genre_scores_gemma":[0.9692458,0.0001881525,0.02868321,0.00004038059,0.000005443203,0.00003302999,0.00007995472,0.00001865235,0.00170536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001328536,"threshold_uncertainty_score":0.00376153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530531354034646,"score_gpt":0.2272907527136772,"score_spread":0.2119854391733308,"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."}}