{"id":"W2885017942","doi":"10.21611/qirt.2018.067","title":"Assessment of Oxide Descaler Functionality in a Steel Hot Strip Mill Using Infrared Video Imaging","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 2018 International Conference on Quantitative InfraRed Thermography","topic":"Calibration and Measurement Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Infrared; Mill; Computer science; Oxide; Materials science; Metallurgy; Optics; Mechanical engineering; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003656902,0.0002058115,0.0001354939,0.0004675747,0.0001490767,0.000303269,0.0002798975,0.0002334787,0.001095997],"category_scores_gemma":[0.0006262005,0.0002028111,0.0001114053,0.000255021,0.0002568862,0.0002971627,0.0001782739,0.0004014661,0.0002135778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001700494,"about_ca_system_score_gemma":0.0001532402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008742477,"about_ca_topic_score_gemma":0.002280352,"domain_scores_codex":[0.999806,0.0000114756,0.000009812886,0.00003238498,0.0001188638,0.00002157416],"domain_scores_gemma":[0.9994342,0.0001633484,0.0001355453,0.00004996624,0.0001731711,0.00004379716],"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":[0.0001359032,0.00002397744,0.001425045,0.00003605071,0.000002465537,0.0001251247,0.0001047641,0.0002502384,0.9925211,0.00006457385,0.00004585745,0.005264823],"study_design_scores_gemma":[0.00001037927,0.0006750191,0.04255173,0.00001249801,0.00001439078,0.0003756811,0.0002464764,0.007968052,0.9471064,0.00005674977,0.0009612694,0.00002133196],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890181,0.0001570811,0.009553834,0.00001695029,0.000009761218,0.00002277296,0.00009902863,0.0001117353,0.001010767],"genre_scores_gemma":[0.9813483,0.0001938483,0.01617794,0.00001742232,0.000004861824,0.00001773072,0.0001291962,0.00003341803,0.002077163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001095997,"threshold_uncertainty_score":0.00366652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06462084054497369,"score_gpt":0.3149399014611066,"score_spread":0.2503190609161329,"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."}}