{"id":"W4223569017","doi":"10.3390/curroncol29040220","title":"Serology-Based Model for Personalized Epithelial Ovarian Cancer Risk Evaluation","year":2022,"lang":"en","type":"article","venue":"Current Oncology","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Medicine; Ovarian cancer; Serology; Epithelial ovarian cancer; Cancer; Computational biology; Bioinformatics; Oncology; Internal medicine; Antibody; Immunology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001759615,0.0009856096,0.001155952,0.00132426,0.0004114133,0.001397395,0.0009141781,0.0008069567,0.002231341],"category_scores_gemma":[0.003290297,0.0003306608,0.001107586,0.0005414614,0.0002576374,0.0006132486,0.0007100435,0.001143867,0.0004272053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009105678,"about_ca_system_score_gemma":0.001433342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248136,"about_ca_topic_score_gemma":0.006751117,"domain_scores_codex":[0.9993956,0.0002063806,0.0000467306,0.0001709779,0.0000835226,0.00009676861],"domain_scores_gemma":[0.9989372,0.0006085674,0.0001230343,0.00004434726,0.0002169533,0.00006995365],"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":[0.0004614504,0.0003215342,0.08577811,0.0001177969,0.0004847987,0.0003902327,0.000120483,0.8316852,0.001117313,0.002647409,0.002910359,0.07396519],"study_design_scores_gemma":[0.0000126955,0.00005388618,0.002317166,0.000009348962,0.00005062066,0.00004572777,0.00001043616,0.9961677,0.0000848378,0.001006266,0.0002340689,0.00000733174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3784385,0.00217762,0.6092586,0.001852582,0.0002881619,0.0003038124,0.002039806,0.001479554,0.004161386],"genre_scores_gemma":[0.9740017,0.000433464,0.02206835,0.0001707047,0.0001008004,0.0002219934,0.001093721,0.00003028949,0.001879062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01248136,"threshold_uncertainty_score":0.02481741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1854072797135509,"score_gpt":0.454421895969908,"score_spread":0.269014616256357,"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."}}