{"id":"W2407597134","doi":"10.12943/cnr.2016.00001","title":"ACTIVE SPECTRAL IMAGING NONDESTRUCTIVE EVALUATION (SINDE) CAMERA","year":2016,"lang":"en","type":"article","venue":"CNL Nuclear Review","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories","funders":"","keywords":"Multispectral image; Nondestructive testing; Materials science; Optics; Infrared; Spectral imaging; Computer science; Optoelectronics; Computer vision; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0007194597,0.0004100362,0.0003996459,0.0007163986,0.0002121455,0.0004821068,0.0008087766,0.000618975,0.003350174],"category_scores_gemma":[0.0006931283,0.0002003601,0.0001578924,0.000270818,0.0003853525,0.0007738895,0.0003782939,0.0006936989,0.001233958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003580987,"about_ca_system_score_gemma":0.0004355643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003278223,"about_ca_topic_score_gemma":0.0005785162,"domain_scores_codex":[0.9994746,0.00003909484,0.00001304113,0.00006825625,0.0003766385,0.0000285098],"domain_scores_gemma":[0.9993616,0.0000948842,0.00004328975,0.00004461912,0.0004262529,0.00002946572],"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":[0.00007991508,0.00005059705,0.0003710864,0.0002872642,0.000009341313,0.0002267814,0.00005404984,0.0005652778,0.9055187,0.004081015,0.002596213,0.08615978],"study_design_scores_gemma":[0.0000131591,0.0001762335,0.001172803,0.0000348002,0.00001317019,0.001246216,0.00004799218,0.01083837,0.9596301,0.0003851175,0.02641509,0.0000270786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1352133,0.006431113,0.8145497,0.0007640854,0.0004991784,0.0005854849,0.0005866013,0.002442395,0.03892802],"genre_scores_gemma":[0.3665447,0.004519264,0.590416,0.0003935632,0.0001162222,0.0003294564,0.0004619727,0.0001177348,0.03710109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003350174,"threshold_uncertainty_score":0.0112074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009646161874958592,"score_gpt":0.2419532507436028,"score_spread":0.2323070888686442,"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."}}