{"id":"W2913027157","doi":"10.1101/538512","title":"SUBSTRA: Supervised Bayesian Patient Stratification","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"AI in cancer detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Benchmark (surveying); Bayesian probability; Machine learning; Computer science; Artificial intelligence; Stratification (seeds); Data mining; Biology; Geography","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":[0.00537962,0.0008910893,0.001254863,0.001259066,0.0006379885,0.0008931328,0.001372205,0.001131944,0.002995096],"category_scores_gemma":[0.01178139,0.0005926026,0.001313488,0.0008094007,0.0007983381,0.000804795,0.001814748,0.001858286,0.001574333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006543414,"about_ca_system_score_gemma":0.002830689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003321184,"about_ca_topic_score_gemma":0.007239032,"domain_scores_codex":[0.9970277,0.001939906,0.0001385177,0.0004488865,0.0003392265,0.0001058358],"domain_scores_gemma":[0.9958158,0.002483466,0.000393124,0.0006463981,0.000464884,0.0001962386],"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":[0.001518849,0.0005410312,0.04488238,0.0003800628,0.0007979046,0.0002807276,0.0004688538,0.1462601,0.008187306,0.02713455,0.03484664,0.7347016],"study_design_scores_gemma":[0.0002829683,0.000241956,0.004838271,0.00007125952,0.0001131469,0.0002815795,0.00005897613,0.9085335,0.003972148,0.07266339,0.008887216,0.00005570265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02570962,0.0005212344,0.9670286,0.001076082,0.00008896727,0.0004311673,0.001650791,0.002199736,0.001293859],"genre_scores_gemma":[0.3852226,0.0004025297,0.6014399,0.001373605,0.0003526958,0.001106366,0.00613912,0.0004006963,0.003562455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00537962,"threshold_uncertainty_score":0.02845049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386459170388303,"score_gpt":0.2093865887277793,"score_spread":0.1955219970238962,"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."}}