{"id":"W4406501100","doi":"10.1016/j.ymed.2014.08.026","title":"10.1016/j.ymed.2014.08.026","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Selection (genetic algorithm); Lung cancer; Lung cancer screening; Cancer; Intensive care medicine; Oncology; Internal medicine; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000584106,0.0007669788,0.0004167062,0.001300941,0.000803443,0.002097904,0.0007928647,0.002836941,0.8665236],"category_scores_gemma":[0.001789408,0.0003266755,0.00048017,0.0005845145,0.0006808647,0.001875082,0.001013486,0.001467447,0.7678397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008360386,"about_ca_system_score_gemma":0.00122598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002234892,"about_ca_topic_score_gemma":0.002282819,"domain_scores_codex":[0.999731,0.00002816403,0.0000236539,0.00006719112,0.00007523254,0.00007479088],"domain_scores_gemma":[0.9990865,0.0001579129,0.0001311086,0.00004179796,0.0001682108,0.0004145405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003863795,0.0004093938,0.01308741,0.0004982971,0.00004486894,0.0006375061,0.0001433447,0.0002106011,0.00064469,0.005056602,0.3508898,0.6279911],"study_design_scores_gemma":[0.00009153711,0.0001773823,0.01265082,0.001228546,0.00005268292,0.005209456,0.0004218931,0.0002365696,0.000431973,0.004568919,0.9748994,0.0000309831],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009859541,0.02110663,0.00201196,0.01813195,0.003602057,0.0001195487,0.005400821,0.001335655,0.9384318],"genre_scores_gemma":[0.0358115,0.008606439,0.002008538,0.00398335,0.001406106,0.0001015071,0.003078635,0.0002613557,0.9447426],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1334764,"threshold_uncertainty_score":0.1903878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005947688870833482,"score_gpt":0.211867206392391,"score_spread":0.2059195175215575,"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."}}