{"id":"W2252688557","doi":"","title":"Correlations between U.S. county annual cancer incidence and population density.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Population; Incidence (geometry); Demography; Affect (linguistics); Population density; Cancer incidence; Range (aeronautics); Biology; Ecology; Geography; Physics; Psychology; Sociology","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":[0.000666091,0.0001119003,0.0001560881,0.001218574,0.0001907464,0.0003492514,0.0001663833,0.0001220307,0.002444526],"category_scores_gemma":[0.005108143,0.0001229832,0.0002204993,0.001842427,0.0002250622,0.0002775842,0.0003720463,0.0002935992,0.0002182951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000386279,"about_ca_system_score_gemma":0.0004235012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03230408,"about_ca_topic_score_gemma":0.0738954,"domain_scores_codex":[0.9996088,0.0001348834,0.00004506741,0.0001031334,0.00007426448,0.00003389515],"domain_scores_gemma":[0.9957556,0.001840676,0.00118918,0.0003033445,0.0007411259,0.0001701482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001125999,0.000003858192,0.9959108,0.00001483528,0.00006179516,0.00001015909,0.00003158971,0.0005162141,0.00003332633,0.0002219092,0.0007087294,0.002475578],"study_design_scores_gemma":[0.000001017584,0.000017419,0.9965983,0.000008563535,0.00003423448,0.00006593968,0.0001344649,0.001428992,0.00007761818,0.0002649176,0.001365586,0.000002945307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755185,0.001149006,0.003109035,0.000602938,0.00004948172,0.00001699577,0.01359757,0.00008633172,0.005870213],"genre_scores_gemma":[0.9963529,0.0001961627,0.0004760264,0.00003030121,0.000008224512,0.000007519427,0.002518725,0.00000364271,0.0004063985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03230408,"threshold_uncertainty_score":0.06423211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03213500104307294,"score_gpt":0.2580165715343157,"score_spread":0.2258815704912427,"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."}}