{"id":"W1579253845","doi":"10.1186/1471-2407-5-130","title":"Modeling the effect of age in T1-2 breast cancer using the SEER database","year":2005,"lang":"en","type":"article","venue":"BMC Cancer","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Magyar Tudományos Akadémia","keywords":"Medicine; Breast cancer; Epidemiology; Surgical oncology; Oncology; Internal medicine; Proportional hazards model; Demography; Cancer; Menopause","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":[0.004936481,0.0004697893,0.0006143574,0.000961097,0.0002084856,0.0008114986,0.001012166,0.0006603427,0.001974049],"category_scores_gemma":[0.009976102,0.0002968767,0.001452325,0.001273932,0.0001317203,0.0004953126,0.0005297551,0.000594531,0.0005983952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114751,"about_ca_system_score_gemma":0.001237114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03909632,"about_ca_topic_score_gemma":0.02240513,"domain_scores_codex":[0.9985321,0.0008507704,0.0001053769,0.0002850655,0.0001299696,0.00009682017],"domain_scores_gemma":[0.99421,0.004210958,0.0007845605,0.0003644077,0.0003236347,0.000106354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000834779,0.0002621441,0.5540451,0.0002143645,0.0008615341,0.0002899409,0.0001429892,0.4153381,0.000425316,0.002114017,0.003028295,0.02244345],"study_design_scores_gemma":[0.000197456,0.0004607367,0.1475926,0.00007854655,0.0004705573,0.0003786398,0.0001199788,0.8427474,0.0005312062,0.002839153,0.004526944,0.00005664956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401201,0.0012168,0.02353768,0.0008956527,0.0000505403,0.0002489413,0.0318908,0.0002064152,0.001833157],"genre_scores_gemma":[0.9743318,0.0006075213,0.01083848,0.0001520011,0.00002710466,0.000216189,0.01296477,0.00002961771,0.0008326857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03909632,"threshold_uncertainty_score":0.07773751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02185576294281863,"score_gpt":0.3115274347475786,"score_spread":0.2896716718047599,"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."}}