{"id":"W4294276952","doi":"10.18178/ijmlc.2022.12.5.1107","title":"Lifespan Prediction for Lung and Bronchus Cancer Patients via Machine Learning Techniques","year":2022,"lang":"en","type":"article","venue":"International Journal of Machine Learning and Computing","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Computer science; Lung cancer; Bronchus; Artificial intelligence; Machine learning; Lung; Medicine; Oncology; Internal medicine; Respiratory disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001443742,0.0001269176,0.0002241428,0.0002322261,0.001524809,0.00002757391,0.0001814761,0.00006393296,0.0001071458],"category_scores_gemma":[0.0006069725,0.0001213638,0.00005993119,0.00008177725,0.0000321961,0.0001149262,0.0002958017,0.001735523,4.803144e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002854753,"about_ca_system_score_gemma":0.0001008349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001384267,"about_ca_topic_score_gemma":0.000081155,"domain_scores_codex":[0.9977922,0.0005863777,0.0007593604,0.0001869955,0.0004326605,0.0002424457],"domain_scores_gemma":[0.9974916,0.0008062293,0.0009394959,0.00003798761,0.000625042,0.00009966103],"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":[0.0002129915,0.00003595533,0.8588678,0.00005911437,0.00006167278,0.00000404998,0.003000677,0.003626923,0.0001921218,0.00006391029,0.0001083472,0.1337665],"study_design_scores_gemma":[0.0009456357,0.001103398,0.03458299,0.0005462444,0.00005259424,0.00007049559,0.00216801,0.9126214,0.0001537695,0.0003801188,0.04715709,0.000218272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766635,0.001929349,0.01681069,0.0022011,0.001802747,0.000358742,0.00004513541,0.00008123266,0.0001075369],"genre_scores_gemma":[0.9967044,0.0002580836,0.001408651,0.00036199,0.0009430271,0.00002354174,0.00003767144,0.0000271215,0.0002355294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9089944,"threshold_uncertainty_score":0.9997751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266609773388481,"score_gpt":0.4235129509432974,"score_spread":0.3908468532094126,"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."}}