{"id":"W2012944782","doi":"10.1056/nejmoa1211776","title":"Selection Criteria for Lung-Cancer Screening","year":2013,"lang":"en","type":"article","venue":"New England Journal of Medicine","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":1011,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"National Cancer Institute; National Institutes of Health","keywords":"Medicine; National Lung Screening Trial; Lung cancer screening; Lung cancer; Selection (genetic algorithm); Cancer; Lung; Intensive care medicine; Oncology; Internal medicine; Artificial intelligence","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":[0.0003003273,0.0001126997,0.0003805564,0.0001235422,0.00004428143,0.00001175873,0.00004599497,0.00004307066,0.001722343],"category_scores_gemma":[0.0001367654,0.00006588538,0.00008434752,0.000103642,0.00002703198,0.0001128437,0.00000559103,0.0001360301,0.000001724412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001206657,"about_ca_system_score_gemma":0.0001227307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003169133,"about_ca_topic_score_gemma":0.00002179685,"domain_scores_codex":[0.9990987,0.00002328533,0.0003540089,0.0001010439,0.0002588632,0.0001641523],"domain_scores_gemma":[0.9989374,0.0001396117,0.0002068466,0.00007261323,0.0003783124,0.0002651583],"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":[0.0009480441,0.0001127639,0.09657121,0.0001713175,0.0005990993,0.00002340629,0.0005962573,0.00002586939,0.004980219,0.00006442193,0.4582041,0.4377033],"study_design_scores_gemma":[0.3182836,0.01405126,0.2516064,0.007281373,0.004278436,0.002432065,0.0003287555,0.007068526,0.007805702,0.00121599,0.3852539,0.0003939702],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7793472,0.01430341,0.03270838,0.1677655,0.002767387,0.001410972,0.000005744146,0.00004200604,0.001649402],"genre_scores_gemma":[0.9780256,0.001075392,0.006782619,0.001591826,0.01141184,0.00003588933,0.000005717491,0.00002135333,0.001049734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4373093,"threshold_uncertainty_score":0.9991902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02791214129575182,"score_gpt":0.3568343131699027,"score_spread":0.3289221718741509,"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."}}