{"id":"W3089756171","doi":"10.2196/25337","title":"Correction: A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Baidu","keywords":"Radiomics; Particle swarm optimization; Support vector machine; Computer science; Lymph node metastasis; Degree (music); Node (physics); Medicine; Metastasis; Artificial intelligence; Machine learning; Cancer; Internal medicine; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005190112,0.0001822893,0.0004290359,0.0001561576,0.0001205965,0.00008260107,0.00006295775,0.000143167,0.0000241811],"category_scores_gemma":[0.0005950902,0.0001611469,0.0000674172,0.0003477924,0.0001150044,0.0002855708,0.0000736261,0.0003080508,4.220008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001090306,"about_ca_system_score_gemma":0.0003760909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002218908,"about_ca_topic_score_gemma":7.542682e-7,"domain_scores_codex":[0.9981545,0.0000472502,0.0007128481,0.0001910471,0.0006527377,0.0002415942],"domain_scores_gemma":[0.998861,0.0001052791,0.0002205458,0.0002067604,0.0001621581,0.0004442174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004051789,0.002856401,0.1513964,0.005190856,0.0006089702,0.00004182495,0.01213615,0.7388757,0.01352235,0.0003736365,0.0004745768,0.07411788],"study_design_scores_gemma":[0.002620438,0.00006128183,0.0157003,0.0002965981,0.0002735216,0.0003497552,0.0003522719,0.9792517,0.0009461187,0.000004157616,0.00001345146,0.000130379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4374322,0.00005949695,0.5617945,0.0002266278,0.0001041356,0.000187869,0.00001063572,0.00003349796,0.0001510198],"genre_scores_gemma":[0.8079106,0.00002894513,0.1910483,0.000708689,0.00005882467,0.00002268916,0.0001760285,0.00002167291,0.00002420731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3707462,"threshold_uncertainty_score":0.6571379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03569403278292189,"score_gpt":0.3005518222846627,"score_spread":0.2648577895017408,"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."}}