{"id":"W2047539772","doi":"10.1152/japplphysiol.00382.2004","title":"A compartmental capillary, convolution integration model to investigate nutrient transport and metabolism in vivo from paired indicator/nutrient dilution curves","year":2005,"lang":"en","type":"article","venue":"Journal of Applied Physiology","topic":"Body Contouring and Surgery","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Dilution; Extracellular; Capillary action; Extracellular fluid; Chemistry; Nutrient; Washout; Biological system; Chromatography; Biochemistry; Internal medicine; Biology; Thermodynamics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009312753,0.0006386568,0.0006505179,0.0003883329,0.0004022288,0.0007742616,0.001065663,0.001135981,0.001108486],"category_scores_gemma":[0.002122171,0.0004160728,0.0006810669,0.0005819394,0.0005873543,0.000593324,0.0004994546,0.0009090114,0.000210877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001569594,"about_ca_system_score_gemma":0.001482192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0267324,"about_ca_topic_score_gemma":0.0123394,"domain_scores_codex":[0.9997852,0.00006041139,0.000009357917,0.00006027483,0.000045301,0.00003941901],"domain_scores_gemma":[0.9993272,0.0004423386,0.00005879818,0.00001936098,0.0001252077,0.00002713655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001071014,0.00004590282,0.001141359,0.00003858495,0.00003073094,0.00009330744,0.00007683522,0.9808612,0.005912952,0.005724666,0.0001869319,0.005780326],"study_design_scores_gemma":[0.000002088144,0.000006632457,0.00009805039,5.53129e-7,0.000003664566,0.00000707569,0.000002157675,0.9993328,0.0002091135,0.0002706961,0.00006480345,0.000002335332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1399914,0.0003150306,0.8561687,0.0001778271,0.00002479447,0.00005621121,0.0001332782,0.0002808187,0.002851892],"genre_scores_gemma":[0.9147262,0.0003017383,0.07441147,0.00008620717,0.00002334586,0.0002630323,0.0002383484,0.00008098244,0.009868665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0267324,"threshold_uncertainty_score":0.05315363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830554635491845,"score_gpt":0.2404402965245449,"score_spread":0.2221347501696264,"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."}}