{"id":"W2112708133","doi":"10.1054/bjoc.1999.0985","title":"Reducing DCO registrations through electronic matching of cancer registry data and routine hospital data","year":2000,"lang":"en","type":"article","venue":"British Journal of Cancer","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research","funders":"","keywords":"Medicine; Lung cancer; Cancer registry; Cancer; Colorectal cancer; Breast cancer; Propensity score matching; Surgery; 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":[],"consensus_categories":[],"category_scores_codex":[0.04199436,0.0005849843,0.0008364142,0.005797396,0.0009856378,0.002428221,0.002141044,0.0007405151,0.002904485],"category_scores_gemma":[0.1716251,0.0007557495,0.0009347229,0.01280349,0.0006635484,0.002488335,0.005741108,0.0007059096,0.001426135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001636447,"about_ca_system_score_gemma":0.003474413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150225,"about_ca_topic_score_gemma":0.01056036,"domain_scores_codex":[0.9302098,0.0451218,0.008482168,0.004514865,0.009825231,0.001846035],"domain_scores_gemma":[0.8671728,0.06274374,0.02970758,0.02948754,0.009658427,0.00122984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007868218,0.0004137861,0.7831951,0.0005198814,0.0002281114,0.0001621766,0.002044034,0.002880532,0.001382018,0.002826416,0.00235296,0.2032082],"study_design_scores_gemma":[0.000226233,0.001291116,0.948669,0.0004715294,0.0003826805,0.0007329021,0.00303648,0.01928598,0.004930506,0.002318102,0.01856008,0.00009539306],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041419,0.001094947,0.06669276,0.002130875,0.0002023252,0.006158013,0.003993286,0.0005097828,0.01507602],"genre_scores_gemma":[0.9282761,0.0007475908,0.06022702,0.0006716733,0.0001733816,0.002072612,0.005301421,0.0001193642,0.002410817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04199436,"threshold_uncertainty_score":0.2220901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06283408088926952,"score_gpt":0.3784573577237227,"score_spread":0.3156232768344532,"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."}}