{"id":"W2111952116","doi":"10.1109/icip.2008.4712004","title":"Statistical fusion and sampling of scientific images","year":2008,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Porous medium; Sampling (signal processing); Resolution (logic); Computer science; Scale (ratio); Iterative reconstruction; Image resolution; Fusion; Artificial intelligence; Computer vision; Pattern recognition (psychology); Porosity; Geology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003254137,0.0005194375,0.0009485919,0.001806357,0.0003135432,0.001160014,0.0008850102,0.0007381514,0.0006725839],"category_scores_gemma":[0.00824735,0.0004613828,0.0009590399,0.00153645,0.001627587,0.001538598,0.001607963,0.0008184692,0.000273634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000692921,"about_ca_system_score_gemma":0.0006273139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008881569,"about_ca_topic_score_gemma":0.0006734318,"domain_scores_codex":[0.9980835,0.0006002137,0.0001020491,0.0003391259,0.0007715168,0.0001036319],"domain_scores_gemma":[0.9971841,0.001375454,0.000398761,0.0005620038,0.0003831009,0.00009659675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004594068,0.000113088,0.003433933,0.0003778267,0.0002341027,0.0002665123,0.0002931178,0.4500751,0.05025927,0.1734992,0.001737926,0.3192504],"study_design_scores_gemma":[0.0000117222,0.00005261485,0.001363352,0.00001058644,0.00002097142,0.00009461096,0.0000194766,0.94261,0.00870834,0.04568936,0.00139495,0.00002402437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01526825,0.0002371667,0.98356,0.000139723,0.00001889631,0.00001613959,0.00005632273,0.0001830665,0.0005205232],"genre_scores_gemma":[0.6224975,0.001109889,0.3738664,0.0001643883,0.0002626973,0.000110515,0.0006960051,0.0001200534,0.001172563],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003254137,"threshold_uncertainty_score":0.01720971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04268697786116465,"score_gpt":0.3174551791289261,"score_spread":0.2747682012677615,"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."}}