{"id":"W3162326337","doi":"10.1101/2021.05.14.21257235","title":"Mortality in hemodialysis: Synchrony of biomarker variability indicates a critical transition","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Biomarker; Context (archaeology); Medicine; Hazard ratio; Internal medicine; Warning system; Demography; Biology; Computer science; Confidence interval","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001829297,0.0002049462,0.0004881165,0.00006515306,0.00003724658,0.00003122919,0.0003916267,0.0003115482,0.001027696],"category_scores_gemma":[0.0003185372,0.0001895746,0.0001890219,0.0003330768,0.0004084636,0.00008641763,0.0004915682,0.000346786,0.00001521926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002071455,"about_ca_system_score_gemma":0.00005866417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001885611,"about_ca_topic_score_gemma":0.001540615,"domain_scores_codex":[0.9974175,0.0004949382,0.0006358713,0.0007465942,0.0004431385,0.0002619607],"domain_scores_gemma":[0.9989074,0.0001889249,0.0001437098,0.0006405065,0.00001913672,0.0001003491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008645944,0.0004415041,0.9819761,0.000573189,0.0000346425,0.00004399236,0.0007450153,0.004217369,0.01143965,0.00005716917,0.000003270248,0.0004594293],"study_design_scores_gemma":[0.0001050082,0.00001033695,0.9295201,0.0001987614,0.00005818942,0.000003083662,0.00008677068,0.06675754,0.001230836,0.001825887,0.00000304069,0.0002004141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926662,0.0000826886,0.004969579,0.0002283374,0.0002164034,0.0002627094,0.00004899589,0.00001741049,0.001507637],"genre_scores_gemma":[0.9990887,0.00004383007,0.0007231721,0.00002551442,0.00001304198,0.00005384362,0.00003616448,0.00001126917,0.000004443197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06254017,"threshold_uncertainty_score":0.9998855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01372102675246548,"score_gpt":0.2683311815741077,"score_spread":0.2546101548216422,"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."}}