{"id":"W2100319754","doi":"10.5430/jbgc.v4n1p21","title":"Prognostic value of FDG-PET scans at diagnosis in small cell lung cancer","year":2013,"lang":"en","type":"article","venue":"Journal of Biomedical Graphics and Computing","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Standardized uptake value; Positron emission tomography; Hazard ratio; Stage (stratigraphy); Lung cancer; PET-CT; Nuclear medicine; Imaging biomarker; Radiology; Biomarker; Predictive value; Prospective cohort study; Oncology; Internal medicine; Magnetic resonance imaging; Confidence interval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006365542,0.0001197094,0.0004604509,0.0003886921,0.00006848873,0.00001658903,0.0001198971,0.00005913477,0.00004095986],"category_scores_gemma":[0.0002705255,0.00008364212,0.0001122821,0.0005259505,0.000302516,0.00004107213,0.0001709605,0.0004318909,3.242205e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001008413,"about_ca_system_score_gemma":0.0001951812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005496227,"about_ca_topic_score_gemma":0.00004899537,"domain_scores_codex":[0.9983807,0.00006430328,0.0005963655,0.0001442678,0.0005065593,0.0003078036],"domain_scores_gemma":[0.9985728,0.0004660834,0.0002998194,0.00008554893,0.0002766893,0.0002990896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004215356,0.0002610646,0.9883242,0.0008552077,0.0001617355,0.0001468211,0.0005355137,0.00001653357,0.001069085,0.00006395405,0.002252378,0.006271305],"study_design_scores_gemma":[0.003871265,0.001262595,0.9422736,0.004561881,0.0002803041,0.0002353198,0.0004040338,0.04501708,0.0007828175,0.0004253112,0.0006850985,0.000200734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867869,0.008825316,0.0002289905,0.003643933,0.0001668122,0.0002756276,0.00000375696,0.000005018557,0.00006363079],"genre_scores_gemma":[0.9948524,0.003934279,0.0007293979,0.0002288927,0.0002157724,0.00001020148,0.000001013593,0.0000113855,0.000016692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04605069,"threshold_uncertainty_score":0.3410826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499805748593517,"score_gpt":0.309217830347643,"score_spread":0.2942197728617078,"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."}}