{"id":"W96820521","doi":"10.1007/978-3-319-00876-9_3","title":"Coarse-Resolution Cone-Beam Scanning of Logs Using Eulerian CT Reconstruction. Part II: Hardware Design and Demonstration","year":2013,"lang":"en","type":"book-chapter","venue":"Conference proceedings of the Society for Experimental Mechanics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Eulerian path; Resolution (logic); Beam (structure); High resolution; Computer science; Optics; Cone (formal languages); Computer hardware; Physics; Geology; Remote sensing; Artificial intelligence; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002550721,0.0002727091,0.0004860436,0.00003810255,0.000277487,0.00003121907,0.0001824206,0.0002464031,0.0001033349],"category_scores_gemma":[0.00004566048,0.0002315494,0.000422404,0.00004615656,0.0003806453,0.0001462522,0.0001700436,0.0002790606,5.019301e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001359272,"about_ca_system_score_gemma":0.000182799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001235013,"about_ca_topic_score_gemma":7.688598e-8,"domain_scores_codex":[0.998652,0.00000278476,0.0005218025,0.0003561872,0.000275971,0.0001912392],"domain_scores_gemma":[0.9984344,0.00002649828,0.0007306826,0.0001538414,0.0005457008,0.0001089414],"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":[0.00004855241,0.00007169085,0.000005112464,0.0004872505,0.0002406894,8.072062e-8,0.0006592866,0.000001856112,0.7971303,0.1923024,0.007035672,0.002017005],"study_design_scores_gemma":[0.000985629,0.0005933028,7.037593e-7,0.003856711,0.0007021369,0.0001656754,0.002530885,0.1241114,0.8367939,0.02659012,0.003262619,0.0004069133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.49015,0.009425051,0.405945,0.0082224,0.003146997,0.04358682,0.000888746,0.001280448,0.03735459],"genre_scores_gemma":[0.6395274,0.0005836803,0.3503658,0.000226317,0.0002099384,0.0003599665,0.00005169826,0.0001125592,0.00856262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1657123,"threshold_uncertainty_score":0.9442311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06892370425145013,"score_gpt":0.2930987458773633,"score_spread":0.2241750416259132,"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."}}