{"id":"W2505707497","doi":"10.14288/1.0135586","title":"Informing selective screening through more robust estimation of STI risk","year":2015,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimation; Computer science; Risk analysis (engineering); Medicine; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001508715,0.00005536496,0.0005551303,0.00003519335,0.0001254555,0.00003392733,0.0002841668,0.0001680053,0.00004882511],"category_scores_gemma":[0.02323981,0.0001724278,0.0001335987,0.0003793893,0.0003963906,0.0003953564,0.0001648351,0.0002407822,0.000005287122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007474043,"about_ca_system_score_gemma":0.0001116367,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03873142,"about_ca_topic_score_gemma":0.01020729,"domain_scores_codex":[0.9984045,0.0002744554,0.0003873609,0.0002725609,0.0004502457,0.0002108978],"domain_scores_gemma":[0.9940546,0.004381961,0.0006217982,0.0002836937,0.0005297516,0.0001282497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00008643958,0.0002115296,0.006564033,0.0002465663,0.0001830265,0.00005909282,0.001522651,0.001607265,0.00001153883,0.0002201769,0.004561267,0.9847264],"study_design_scores_gemma":[0.00331908,0.0003375796,0.5191475,0.0006355966,0.0003792239,0.00003931554,0.00496168,0.02023257,0.00001579362,0.4505577,0.00003499314,0.0003390455],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4857714,0.00001685085,0.5121379,0.00002226842,0.00008506737,0.0002458759,0.0002154154,0.00005235952,0.00145278],"genre_scores_gemma":[0.4561449,0.00001281341,0.543731,0.000007951598,0.00002024743,3.287452e-7,0.000002941179,0.00001035656,0.0000694933],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9843873,"threshold_uncertainty_score":0.9849879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2556070586823056,"score_gpt":0.3873188887084527,"score_spread":0.1317118300261471,"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."}}