{"id":"W2552299662","doi":"10.1200/jco.2016.69.2855","title":"National Cancer Data Base: An Important Research Tool, but Not Population-Based","year":2017,"lang":"en","type":"letter","venue":"Journal of Clinical Oncology","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre","funders":"","keywords":"Medicine; Cancer; Population; Base (topology); Environmental health; Internal medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02445382,0.0004075248,0.001146935,0.003407549,0.001635921,0.005350593,0.002140365,0.008815721,0.008700985],"category_scores_gemma":[0.1248729,0.000680555,0.0005730475,0.006952004,0.001536711,0.007097215,0.002746074,0.01171397,0.00668883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004695944,"about_ca_system_score_gemma":0.008237481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009350102,"about_ca_topic_score_gemma":0.01642009,"domain_scores_codex":[0.9763051,0.01063845,0.005114139,0.001056693,0.006211317,0.0006742295],"domain_scores_gemma":[0.8294677,0.1026808,0.01571835,0.008977694,0.03388962,0.009265808],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008268505,0.00003938145,0.01261079,0.0002123873,0.00004571221,0.000451161,0.0001817794,0.0001090688,0.00009723995,0.00357545,0.9528845,0.02970989],"study_design_scores_gemma":[0.0001943176,0.00007654246,0.01443117,0.001626639,0.0000932041,0.001407678,0.001158539,0.0007782212,0.0003893781,0.008488791,0.9712718,0.00008377348],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.001576362,0.001223619,0.0005907318,0.9768196,0.005366296,0.00005633495,0.007050248,0.00006237887,0.007254413],"genre_scores_gemma":[0.038135,0.006158085,0.006920321,0.8972382,0.02986882,0.0005656977,0.01253098,0.0002194058,0.008363552],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.9755462,"threshold_uncertainty_score":0.1293257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7596819512929659,"score_gpt":0.6551424435805348,"score_spread":0.1045395077124311,"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."}}