{"id":"W3012071714","doi":"10.5220/0008857302950302","title":"Advanced Analytics to Predict Survivability of Breast Cancer Patients","year":2020,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Survivability; Computer science; Breast cancer; Analytics; Cancer; Medicine; Data science; Internal medicine; Computer network","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":[0.0007279293,0.0004521882,0.0004050061,0.002230263,0.0002118258,0.00114976,0.0003691588,0.0004603076,0.002041797],"category_scores_gemma":[0.005759187,0.00009910575,0.0004865681,0.001268284,0.0001092545,0.0007107639,0.0005910052,0.0007731885,0.0006661247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000375825,"about_ca_system_score_gemma":0.0006432551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004609587,"about_ca_topic_score_gemma":0.005523405,"domain_scores_codex":[0.999466,0.0001320135,0.00005757974,0.00009379465,0.0001633074,0.00008733472],"domain_scores_gemma":[0.9971703,0.001645779,0.0003999246,0.0001594087,0.0004186963,0.0002059741],"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":[0.0007974259,0.0008788792,0.7004468,0.0002445557,0.0003462511,0.0003532166,0.0002681496,0.03319979,0.001951311,0.002808347,0.01997801,0.2387273],"study_design_scores_gemma":[0.00008489542,0.0009774511,0.2487244,0.0002790931,0.0003222785,0.0008298203,0.001499387,0.7030673,0.004348748,0.02447409,0.0153323,0.00006017456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9200303,0.003641253,0.03714364,0.006288332,0.0003773021,0.0002302207,0.01992303,0.001145974,0.01121997],"genre_scores_gemma":[0.9846156,0.0004783233,0.006554407,0.0001934312,0.0001173425,0.00003275636,0.007208081,0.00001275811,0.0007872849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004609587,"threshold_uncertainty_score":0.009165525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1559165194323481,"score_gpt":0.4872915018489559,"score_spread":0.3313749824166078,"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."}}