{"id":"W2078198143","doi":"10.1053/jpsu.2001.25806","title":"Multislice helical CT depiction of Wilms' Tumor","year":2001,"lang":"en","type":"article","venue":"Journal of Pediatric Surgery","topic":"Renal and related cancers","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Children's Hospital","funders":"","keywords":"Medicine; Wilms' tumor; Detector; Radiology; Helical computed tomography; Tomography; Depiction; Nuclear medicine; Row; Image quality; Computed tomography; Artificial intelligence; Optics; Computer science; Pathology; Image (mathematics); 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":[0.0002217263,0.0006065813,0.0002759926,0.001690795,0.0003175509,0.0003647362,0.0005067912,0.001880572,0.005020914],"category_scores_gemma":[0.001072892,0.0007223296,0.000314698,0.0006326197,0.0003246295,0.0008380062,0.0003549803,0.001290561,0.0007171616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003865728,"about_ca_system_score_gemma":0.00037051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474884,"about_ca_topic_score_gemma":0.002000956,"domain_scores_codex":[0.9999263,0.00001069279,0.00001401003,0.00001209383,0.00001427301,0.00002251367],"domain_scores_gemma":[0.9995401,0.0002101316,0.00004915937,0.00004670037,0.00004214315,0.0001117227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"observational","study_design_scores_codex":[0.002683599,0.0002155749,0.03389612,0.0004686413,0.0001125845,0.7621277,0.0002833503,0.01164632,0.1429459,0.003924128,0.008655966,0.03304014],"study_design_scores_gemma":[0.0002783425,0.000684313,0.1274031,0.000236425,0.000213219,0.7908169,0.000156792,0.01909076,0.04836199,0.00129975,0.01138563,0.00007268065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8980609,0.01035611,0.01666008,0.006038861,0.0004321051,0.0002965479,0.003005827,0.0008216235,0.06432797],"genre_scores_gemma":[0.980456,0.003017695,0.01120683,0.000634099,0.0005566799,0.00003827616,0.0005297535,0.00007771148,0.003483005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005020914,"threshold_uncertainty_score":0.01679665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029597707013987,"score_gpt":0.237086521434087,"score_spread":0.2267905443639471,"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."}}