{"id":"W2015140470","doi":"10.1159/000368701","title":"Impact of Antibiotic Treatment Intensity on Long-Term Sepsis-Associated Kidney Injury in a Polymicrobial Peritoneal Contamination and Infection Model","year":2015,"lang":"en","type":"article","venue":"The Nephron journals/Nephron journals","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Berger (Canada)","funders":"Bundesministerium für Bildung und Forschung","keywords":"Medicine; Sepsis; Creatinine; Acute kidney injury; Kidney; Internal medicine; Kidney disease; Urinary system; Urine; Renal function; Antibiotics; Peritonitis; Gastroenterology; Urology; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002713094,0.0005920317,0.001272401,0.00122152,0.0002892136,0.0002112253,0.0002514358,0.0004283231,0.0002575647],"category_scores_gemma":[0.0007071416,0.0004049633,0.0004975978,0.000823873,0.0003448404,0.0005668782,0.0001330919,0.001179433,0.00002963948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003596479,"about_ca_system_score_gemma":0.002035146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007101017,"about_ca_topic_score_gemma":0.0001722266,"domain_scores_codex":[0.9953316,0.0007673359,0.001330093,0.0004842176,0.001181785,0.0009049697],"domain_scores_gemma":[0.9958284,0.0001315495,0.0009917424,0.0005508774,0.001103126,0.001394342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007629471,0.002836001,0.7909051,0.00007831157,0.001417643,0.000260607,0.003156211,0.000206225,0.154303,0.000004512853,0.02423004,0.01497298],"study_design_scores_gemma":[0.01181471,0.008690974,0.9571195,0.001627865,0.0005167234,0.001802895,0.0001877659,0.008189144,0.009383747,0.0001014815,0.0001152367,0.0004499653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942008,0.0004746405,0.0002335224,0.003216255,0.0002771661,0.001033687,0.0002349199,0.00004584718,0.0002831877],"genre_scores_gemma":[0.9961396,0.001789966,0.00006921923,0.0009172542,0.0003928817,0.00001383696,0.00007538823,0.00008293596,0.0005188833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1662145,"threshold_uncertainty_score":0.9998402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0638059377087201,"score_gpt":0.3888593028941905,"score_spread":0.3250533651854703,"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."}}