{"id":"W7073606836","doi":"","title":"Contribution of an intrinsic lag of continuous glucose monitoring systems to differences in measured and actual glucose concentrations changing at variable rates in vitro","year":2010,"lang":"en","type":"article","venue":"UWA Profiles and Research Repository (UWA)","topic":"Photorefractive and Nonlinear Optics","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Lag; Continuous glucose monitoring; Time lag; Variable (mathematics); Lag time","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":[0.000807491,0.0001171915,0.0003261834,0.0002177582,0.0001793859,0.00007489538,0.000103494,0.00007971994,0.000003060442],"category_scores_gemma":[0.00009230078,0.0001003588,0.00002176764,0.0002832595,0.0001477297,0.0001888614,0.0001074925,0.0003315625,4.029385e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004114749,"about_ca_system_score_gemma":0.0001062761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001243377,"about_ca_topic_score_gemma":0.000005106751,"domain_scores_codex":[0.9985855,0.0002297494,0.000318976,0.0002465253,0.0002730008,0.0003462826],"domain_scores_gemma":[0.9989452,0.000281703,0.0001145679,0.0001626987,0.0003633517,0.0001325283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001966966,0.0001615458,0.1445729,0.0000492837,0.00002316813,0.000004068494,0.0008095215,0.000002407404,0.8529086,0.0007258476,0.000001202176,0.0005447221],"study_design_scores_gemma":[0.0006548713,0.0001557584,0.03412117,0.0001402026,0.000008058417,0.000002336946,0.002516168,0.001571417,0.9606017,0.00007594255,0.00005610263,0.00009623032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985441,0.000397095,0.00004975121,0.00001495704,0.0001818433,0.0006030414,0.00006173195,0.00000591539,0.0001415916],"genre_scores_gemma":[0.9993137,0.00003001572,0.0002191065,8.006827e-7,0.0002436359,0.00008096985,0.00003331816,0.000009425794,0.00006904839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1104518,"threshold_uncertainty_score":0.4092515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02434425780759547,"score_gpt":0.3057534028757938,"score_spread":0.2814091450681984,"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."}}