{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04823251,0.001207614,0.002147801,0.002117968,0.00083103,0.001386179,0.001864498,0.001804021,0.006274709],"category_scores_gemma":[0.1327947,0.0004055303,0.002947445,0.001715897,0.0007992134,0.0007953554,0.001641463,0.001906532,0.001357021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229135,"about_ca_system_score_gemma":0.004164927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002435698,"about_ca_topic_score_gemma":0.002567577,"domain_scores_codex":[0.9417323,0.03579619,0.008066771,0.003153839,0.009686182,0.001564646],"domain_scores_gemma":[0.9378816,0.04007841,0.008577539,0.00517309,0.006633042,0.001656395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01401953,0.0007609511,0.766907,0.002665787,0.00276278,0.001379424,0.0009092271,0.01595537,0.001947293,0.0106328,0.04370838,0.1383514],"study_design_scores_gemma":[0.01024415,0.00827428,0.5315065,0.004666977,0.005722465,0.007517562,0.0006101173,0.222365,0.01029054,0.0573108,0.141042,0.0004496727],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6077445,0.01332132,0.2580201,0.01349314,0.003269805,0.04589776,0.02544788,0.001397796,0.03140759],"genre_scores_gemma":[0.9218506,0.0008315625,0.04779643,0.0036208,0.0006567892,0.01385177,0.008949541,0.0001507434,0.002291715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04823251,"threshold_uncertainty_score":0.2550809,"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."}}