{"id":"W4398933069","doi":"10.7910/dvn/zh4m1a","title":"Cancer in North America Database","year":2011,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Database; Geography; History; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001868277,0.0008003291,0.001858091,0.007199171,0.001397757,0.003220589,0.00275093,0.001166215,0.257706],"category_scores_gemma":[0.01243991,0.0005687493,0.0009002172,0.01584,0.0002977398,0.001889445,0.002199403,0.001560641,0.09567767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005204796,"about_ca_system_score_gemma":0.01067576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08673615,"about_ca_topic_score_gemma":0.08911649,"domain_scores_codex":[0.9974051,0.0004478682,0.0006510966,0.0006005188,0.0006376865,0.0002577418],"domain_scores_gemma":[0.9903645,0.001436761,0.0008874212,0.0009697041,0.005412866,0.0009287031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005455076,0.00001070059,0.0008015023,0.0005010607,0.00002432963,0.00002420133,0.00003632454,0.00003135453,0.00002290427,0.0009506639,0.9889397,0.008602661],"study_design_scores_gemma":[0.00009046076,0.00001000946,0.005687543,0.0005922641,0.00003880523,0.0000814603,0.00009653846,0.0000701363,0.00006146683,0.0007620208,0.9924907,0.00001854601],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003986056,0.001260538,0.0002688961,0.00139615,0.0002025517,0.0001958805,0.9610345,0.0006495981,0.03459327],"genre_scores_gemma":[0.002539617,0.002244484,0.001220274,0.001508474,0.0001792771,0.001198676,0.9724158,0.0004353875,0.01825807],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9132639,"threshold_uncertainty_score":0.8621125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03309958530554212,"score_gpt":0.2352890051569986,"score_spread":0.2021894198514564,"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."}}