{"id":"W2549772348","doi":"10.3390/met6110272","title":"Crack Detection Method Applied to 3D Computed Tomography Images of Baked Carbon Anodes","year":2016,"lang":"en","type":"article","venue":"Metals","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Anode; Materials science; Computed tomography; Resolution (logic); Tomography; Carbon fibers; Nondestructive testing; Percolation (cognitive psychology); Composite material; Computer science; Artificial intelligence; Optics; Radiology; Electrode; 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":[0.0002863352,0.0004300446,0.0002364925,0.001282233,0.0001898788,0.0006398521,0.0003826428,0.0006603559,0.001307751],"category_scores_gemma":[0.001103803,0.0004007541,0.0002236853,0.0005080485,0.0003151108,0.0002848385,0.0003432656,0.0004216066,0.0002998098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003018349,"about_ca_system_score_gemma":0.0005974396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001737566,"about_ca_topic_score_gemma":0.002605607,"domain_scores_codex":[0.9998305,0.00001448202,0.00001277656,0.00004635156,0.00007609638,0.00001987756],"domain_scores_gemma":[0.9995673,0.0001362556,0.00005221794,0.00005344759,0.0001648259,0.00002603174],"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":[0.0000888909,0.00002487961,0.002763509,0.0001593938,0.000017578,0.000588792,0.0001733356,0.01017931,0.9319439,0.0009945562,0.0003694004,0.05269651],"study_design_scores_gemma":[0.00002503134,0.00009830982,0.02104731,0.00004393079,0.00003865607,0.002027315,0.0001723781,0.3131111,0.6579164,0.0008172342,0.00461771,0.00008463392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2769028,0.000321288,0.7184125,0.0001730389,0.00004182501,0.0002661351,0.0005038073,0.001617368,0.001761224],"genre_scores_gemma":[0.423309,0.0003044857,0.5748463,0.00004958339,0.00001153101,0.0001272083,0.0002946106,0.0001422698,0.0009149287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001737566,"threshold_uncertainty_score":0.004374862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007204551584076809,"score_gpt":0.2184473070352851,"score_spread":0.2112427554512082,"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."}}