{"id":"W2809338510","doi":"10.1016/j.pmedr.2018.06.010","title":"Estimating lifetime and 10-year risk of lung cancer","year":2018,"lang":"en","type":"article","venue":"Preventive Medicine Reports","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Lung cancer; Medicine; Environmental health; Oncology; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008698152,0.0001408482,0.0004392292,0.00008570236,0.00007827633,0.000003942477,0.00003982344,0.00005452972,0.00121876],"category_scores_gemma":[0.00132673,0.0001047508,0.00005741927,0.0002061648,0.0003725508,0.0000636211,0.00006503297,0.0001366155,0.00000285788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005247747,"about_ca_system_score_gemma":0.00012016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001003653,"about_ca_topic_score_gemma":0.00002741762,"domain_scores_codex":[0.9984742,0.00005118316,0.0005149665,0.000320742,0.0004313157,0.0002076208],"domain_scores_gemma":[0.9985706,0.00006603219,0.0005224694,0.0002743562,0.0004061368,0.0001603921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001327781,0.00002187151,0.9742996,0.0002014199,0.000275514,0.0001856741,0.0008762125,0.000005398639,0.00131821,0.00002029692,0.0102099,0.01245312],"study_design_scores_gemma":[0.002156352,0.001834881,0.9661279,0.007599601,0.002334563,0.001198251,0.000566335,0.007019826,0.006571072,0.001486175,0.002768395,0.0003366125],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781668,0.004480183,0.002430568,0.0004736747,0.0004130779,0.0004167279,0.000004507097,0.00004153127,0.01357295],"genre_scores_gemma":[0.9937919,0.0001401261,0.003541366,0.00009708278,0.0009718885,0.00002016443,0.000006473389,0.00001525925,0.001415761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01562509,"threshold_uncertainty_score":0.9996943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0309133753789626,"score_gpt":0.3757505766724804,"score_spread":0.3448372012935177,"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."}}