{"id":"W4393227855","doi":"10.54254/2755-2721/53/20241290","title":"Application of machine learning in lung cancer prediction","year":2024,"lang":"en","type":"article","venue":"Applied and Computational Engineering","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Machine learning; Artificial intelligence; Computer science; Lung cancer; Medicine; Pathology","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":[0.001641397,0.0007403077,0.0009564939,0.00170896,0.0002832602,0.001323539,0.000828807,0.001052134,0.001060225],"category_scores_gemma":[0.005873635,0.0002881632,0.0008934601,0.001739274,0.0004209952,0.0008941274,0.0005195373,0.001383718,0.0005493734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000662904,"about_ca_system_score_gemma":0.0008416958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003476579,"about_ca_topic_score_gemma":0.001979274,"domain_scores_codex":[0.9990939,0.0003543115,0.00006531217,0.0001705073,0.0002571304,0.00005888472],"domain_scores_gemma":[0.9976072,0.001739747,0.0001390656,0.00009411364,0.000375304,0.00004457352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009864433,0.0001769472,0.02404578,0.0007960346,0.000423329,0.0003095086,0.0001030787,0.3950042,0.001566992,0.01544014,0.00948378,0.5525516],"study_design_scores_gemma":[0.000008362292,0.00007787882,0.003704642,0.0001803442,0.00007397937,0.0001613283,0.00004266508,0.9619384,0.001728288,0.02341317,0.008637322,0.0000335837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0502072,0.07915395,0.8507223,0.00499401,0.0009089275,0.0001359466,0.0007036654,0.001229986,0.01194395],"genre_scores_gemma":[0.782642,0.04238025,0.167107,0.0007903234,0.001087208,0.0001657482,0.00107834,0.00009597215,0.004653195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003476579,"threshold_uncertainty_score":0.008680642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003001213330371544,"score_gpt":0.2400718195270839,"score_spread":0.2370706061967123,"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."}}