{"id":"W3181988278","doi":"","title":"Lung Cancer Risk and Life-Expectancy-Based Models for Lung Cancer Screening Selection","year":2021,"lang":"en","type":"article","venue":"SFU Undergraduate Research Symposium Journal","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lung cancer; Life expectancy; Lung cancer screening; Medicine; Cancer; False positive paradox; Cancer screening; Intensive care medicine; Incidence (geometry); Oncology; Internal medicine; Environmental health; Population; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001117115,0.0003013102,0.0005174531,0.0003905406,0.001226983,0.0003390426,0.0001188024,0.0001503951,0.0001084899],"category_scores_gemma":[0.0001710873,0.0002509528,0.0002677492,0.0006922756,0.000116714,0.000318561,0.00007216866,0.001079284,8.627547e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777421,"about_ca_system_score_gemma":0.003446853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009635875,"about_ca_topic_score_gemma":0.0008546164,"domain_scores_codex":[0.9962828,0.0004225358,0.0004723424,0.0006427949,0.001164039,0.001015446],"domain_scores_gemma":[0.9965666,0.0004805097,0.0002024191,0.0002645633,0.001652478,0.000833416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003535622,0.001556978,0.7393487,0.00308082,0.006829403,0.0005904507,0.001183922,0.1035123,0.01382821,0.003025465,0.1041706,0.01933749],"study_design_scores_gemma":[0.0180856,0.001110793,0.006301064,0.004211182,0.002141011,0.0003451347,0.000411882,0.9403597,0.01869051,0.004067416,0.003596023,0.0006797158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2863541,0.1881051,0.1880791,0.3284741,0.001621913,0.004520146,0.0004073288,0.0002424446,0.002195713],"genre_scores_gemma":[0.9161356,0.07674643,0.003618757,0.000366981,0.001279453,0.0007831074,0.00002883085,0.00009100365,0.0009498382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8368474,"threshold_uncertainty_score":0.9999943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04518276651877581,"score_gpt":0.3944460804132629,"score_spread":0.3492633138944871,"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."}}