{"id":"W2510953245","doi":"10.1016/j.ijthermalsci.2016.08.007","title":"Volume or inside heating thermography using electromagnetic excitation for advanced composite materials","year":2016,"lang":"en","type":"article","venue":"International Journal of Thermal Sciences","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"China Scholarship Council; University of British Columbia; National Natural Science Foundation of China; Newcastle University","keywords":"Thermography; Materials science; Microwave; Composite material; Delamination (geology); Terahertz radiation; Heating element; Thermal conduction; Optics; Infrared; Optoelectronics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001724947,0.0001729821,0.0001574675,0.0002208515,0.0001754368,0.0003001355,0.0002255415,0.0002513511,0.001354929],"category_scores_gemma":[0.0002315135,0.000209134,0.0001480797,0.0001799722,0.0003160287,0.0004316272,0.0002513693,0.000354654,0.0002018665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125458,"about_ca_system_score_gemma":0.0001104243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000137793,"about_ca_topic_score_gemma":0.0003921546,"domain_scores_codex":[0.9998897,0.00002525654,0.000003355615,0.00003129277,0.00003718917,0.00001322535],"domain_scores_gemma":[0.9998351,0.00007131419,0.00003513776,0.00002487334,0.00002624384,0.000007283578],"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":[0.00009981694,0.00001076912,0.0002861529,0.00006241597,0.000003306115,0.00002755294,0.00004803193,0.0004491315,0.990399,0.0005047328,0.00007135521,0.008037807],"study_design_scores_gemma":[0.000002370319,0.00004208368,0.0009692119,0.000004288386,0.000005623977,0.00004771931,0.00001366669,0.003723948,0.9944859,0.00003884936,0.0006625932,0.000003740304],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9047905,0.001847104,0.08418839,0.00008643982,0.00007415112,0.00002650418,0.0000866193,0.0004419028,0.008458587],"genre_scores_gemma":[0.979255,0.0002838341,0.01785096,0.00002438409,0.00001298825,0.00001203987,0.00003129755,0.00005672142,0.002472879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001354929,"threshold_uncertainty_score":0.004532695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767312402014574,"score_gpt":0.2787851886898074,"score_spread":0.2611120646696616,"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."}}