{"id":"W1496249891","doi":"10.1159/000081649","title":"Patient Recruitment and Selection","year":2004,"lang":"en","type":"review","venue":"Contributions to nephrology","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre","funders":"","keywords":"Selection (genetic algorithm); Psychology; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000185871,0.0002854624,0.002196672,0.0002432403,0.0001120375,0.00001527128,0.00003911387,0.0004469645,0.00009851464],"category_scores_gemma":[0.0002967526,0.0002166646,0.0005740658,0.0003238552,0.00006953569,0.00001777348,0.00005038379,0.0003182337,0.0002256177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005462956,"about_ca_system_score_gemma":0.0004497386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002281779,"about_ca_topic_score_gemma":0.000007654004,"domain_scores_codex":[0.9984812,0.0001990877,0.000450245,0.0003844788,0.0001278418,0.0003571835],"domain_scores_gemma":[0.9989195,0.0003511251,0.0001027447,0.0001870235,0.0001433741,0.0002962552],"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":[0.00005976009,0.0001055528,0.00002451586,0.001355376,0.0004512139,0.0001536158,0.00003395584,0.00000108783,0.000002211788,0.01341009,0.001251165,0.9831514],"study_design_scores_gemma":[0.000541389,0.0005597058,0.000179685,0.001215691,0.001650828,0.002043988,0.000002769447,4.633277e-7,9.494701e-7,0.00003090194,0.993598,0.0001756457],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004223534,0.9939899,0.0002855973,0.001744044,0.0001430057,0.002960581,0.00007438875,0.00007762349,0.0006826313],"genre_scores_gemma":[0.0000624804,0.9964453,0.0001780979,0.001440916,0.0001980984,0.000852595,0.0001752115,0.00002391504,0.0006233646],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9923468,"threshold_uncertainty_score":0.8835325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0410246122990894,"score_gpt":0.3725758574674807,"score_spread":0.3315512451683914,"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."}}