{"id":"W3209171793","doi":"10.1177/15330338211050767","title":"Prognosticating Outcome in Pancreatic Head Cancer With the use of a Machine Learning Algorithm","year":2021,"lang":"en","type":"article","venue":"Technology in Cancer Research & Treatment","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Pancreaticoduodenectomy; Medicine; Algorithm; Pancreatic cancer; Retrospective cohort study; Cohort; Adenocarcinoma; Machine learning; Pancreatic head; Artificial intelligence; Cancer; Surgery; Internal medicine; Resection; Computer science","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":[0.001201371,0.0003118826,0.0002662082,0.001091019,0.0001784376,0.0004640405,0.0002721414,0.0002901451,0.0006919479],"category_scores_gemma":[0.00520102,0.00008748731,0.0003253995,0.0004321272,0.0001959303,0.0003252457,0.0002572398,0.0003680731,0.0001826612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002782728,"about_ca_system_score_gemma":0.0005004515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006938828,"about_ca_topic_score_gemma":0.0008373421,"domain_scores_codex":[0.9996556,0.0001584273,0.00003704663,0.00004500135,0.00006858661,0.00003522364],"domain_scores_gemma":[0.9978737,0.001249406,0.0004534594,0.0001043673,0.0002438316,0.00007521117],"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":[0.0006327393,0.0002988472,0.8787461,0.0000415847,0.0001136857,0.0001287469,0.00004665992,0.01460151,0.002254271,0.00017933,0.0006733744,0.1022832],"study_design_scores_gemma":[0.0002609803,0.001994426,0.5737928,0.00009417125,0.0003396913,0.002036619,0.000228798,0.4036275,0.01071462,0.004059007,0.002792636,0.00005876003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773642,0.0003223867,0.02087412,0.0002420952,0.00002103683,0.00006413574,0.0002254022,0.0001020508,0.000784477],"genre_scores_gemma":[0.9826498,0.00009298554,0.01662052,0.0000295407,0.00002574267,0.00004391861,0.0003816033,0.000005993555,0.0001499282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001201371,"threshold_uncertainty_score":0.006353557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2038617164271218,"score_gpt":0.4785597273621083,"score_spread":0.2746980109349865,"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."}}