{"id":"W6967050286","doi":"10.48321/d1f8a3d88d","title":"Supporting Genomic Testing in Breast, Ovarian and Endometrial Cancer","year":2024,"lang":"en","type":"other","venue":"California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Endometrial cancer; Genetic testing; Ovarian cancer; Personalized medicine; Cancer; Germline; Test (biology); Precision medicine; Epithelial ovarian cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01184197,0.0004705505,0.0003550896,0.000948812,0.001342354,0.002503326,0.001633942,0.001591474,0.01229446],"category_scores_gemma":[0.07452482,0.0002651077,0.0007502043,0.0005802006,0.0008584323,0.002546563,0.004832562,0.001847372,0.002691439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002196445,"about_ca_system_score_gemma":0.008873686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005693927,"about_ca_topic_score_gemma":0.01240525,"domain_scores_codex":[0.986089,0.009828924,0.0009569626,0.0006831855,0.001624584,0.0008173112],"domain_scores_gemma":[0.9518745,0.03632489,0.002724249,0.002013741,0.002979772,0.004082922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007785778,0.002149001,0.06038582,0.001086314,0.00007240057,0.00132117,0.01211029,0.003309536,0.001895785,0.005279614,0.06745713,0.8441544],"study_design_scores_gemma":[0.00133028,0.004395631,0.05248155,0.005730385,0.0005230697,0.004404336,0.02648795,0.03521219,0.01622888,0.05041378,0.8021479,0.0006441567],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5871558,0.006823136,0.1087651,0.1212303,0.001683892,0.005648341,0.004598938,0.009163146,0.1549313],"genre_scores_gemma":[0.7423581,0.004023266,0.218015,0.01931546,0.0005298751,0.002386037,0.002139031,0.0003315115,0.01090163],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01229446,"threshold_uncertainty_score":0.06262708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571740383098434,"score_gpt":0.2457670081669007,"score_spread":0.2300496043359163,"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."}}