{"id":"W4362089916","doi":"","title":"COMPUTER-AIDED DETECTION OF ACINAR SHADOWS IN CHEST RADIOGRAPHS","year":2013,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Radiography; Computer science; Radiology; Medicine; Nuclear medicine; Computer graphics (images)","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":[0.0004994729,0.0003109287,0.000450491,0.002051244,0.0001349252,0.00062805,0.0004165374,0.0005563181,0.001602307],"category_scores_gemma":[0.001979531,0.0002189021,0.0002352908,0.0005998737,0.0001572141,0.000284532,0.0003159636,0.0002262632,0.0008550476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001469742,"about_ca_system_score_gemma":0.0002429966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001441419,"about_ca_topic_score_gemma":0.002244295,"domain_scores_codex":[0.9996062,0.00008518196,0.00003280795,0.00006195836,0.000183038,0.0000308508],"domain_scores_gemma":[0.999134,0.000345147,0.0000997462,0.00008047438,0.0003045883,0.0000361876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008619557,0.0001854227,0.01622964,0.0005094325,0.00007085694,0.0009889031,0.0001540402,0.01254518,0.356846,0.0003888445,0.002936021,0.6082836],"study_design_scores_gemma":[0.00008514505,0.0004972846,0.138524,0.00009979444,0.0001288967,0.006048667,0.00023558,0.6355317,0.2104066,0.0006355143,0.007732491,0.00007427453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5059164,0.003287395,0.4796517,0.0002465732,0.0001411742,0.0003190829,0.0007075008,0.006186722,0.003543484],"genre_scores_gemma":[0.7945347,0.001063692,0.2017471,0.00007503358,0.00006680259,0.00005811825,0.0005606383,0.00007677721,0.001817146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002051244,"threshold_uncertainty_score":0.005360305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1527252885005288,"score_gpt":0.5018151435330974,"score_spread":0.3490898550325686,"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."}}