{"id":"W2041337540","doi":"10.1371/journal.pone.0067025","title":"Numerical Modeling of Interstitial Fluid Flow Coupled with Blood Flow through a Remodeled Solid Tumor Microvascular Network","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mechanics; Blood flow; Sprouting angiogenesis; Flow (mathematics); Fluid dynamics; Capillary action; Interstitial fluid; Extravasation; Conservation of mass; Physics; Materials science; Angiogenesis; Medicine; Thermodynamics; Pathology; Neovascularization; Cardiology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000326513,0.0003802826,0.001197249,0.00004987509,0.00009521509,0.00003365052,0.0004074701,0.0001446268,0.0006175465],"category_scores_gemma":[0.0005085494,0.0002912724,0.0001954709,0.0002485027,0.0001714544,0.0001699104,0.0001382805,0.0003521583,0.0001241837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003959405,"about_ca_system_score_gemma":0.00006783596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005308273,"about_ca_topic_score_gemma":0.000006488236,"domain_scores_codex":[0.9974051,0.00013031,0.0008093189,0.0004794157,0.0005313209,0.0006445629],"domain_scores_gemma":[0.9981369,0.000373094,0.0002237641,0.0007633989,0.0003526388,0.0001501979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004223053,0.07552864,0.001989834,0.02374571,0.04052352,0.0007088834,0.01466473,0.1798241,0.5694544,0.08286711,0.006124845,0.0003451757],"study_design_scores_gemma":[0.001354826,0.0004085843,0.000002040147,0.0008735772,0.0007902552,0.00004116654,0.0000465266,0.9134246,0.01561088,0.06711244,6.678022e-7,0.0003345107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7335781,0.0001079682,0.2642789,0.0001636208,0.00002874989,0.0009222302,0.00000640195,0.00016944,0.0007445618],"genre_scores_gemma":[0.5648331,0.000009830841,0.4346631,0.0001149915,0.0001602949,0.0001067436,0.00001164932,0.00006031005,0.00004000921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7336004,"threshold_uncertainty_score":0.9999539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04277822892211536,"score_gpt":0.2407511176332761,"score_spread":0.1979728887111607,"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."}}