{"id":"W2125905810","doi":"10.1002/bit.23183","title":"Pore‐network modeling of biofilm evolution in porous media","year":2011,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Mass transfer; Porous medium; Biofilm; Permeability (electromagnetism); Diffusion; Hydraulic conductivity; Advection; Chemistry; Porosity; Biomass (ecology); Mass transfer coefficient; Chemical engineering; Environmental science; Materials science; Soil science; Thermodynamics; Chromatography; Membrane; Ecology; Geology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001243714,0.0001428765,0.0002015488,0.0003103716,0.00001308477,0.000002210614,0.0001209306,0.0004228103,0.000005192489],"category_scores_gemma":[0.00001994159,0.0001513094,0.00002329039,0.0003438698,0.00005538107,0.00008278239,0.00004420642,0.000243235,0.00000124539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004604838,"about_ca_system_score_gemma":0.000005566622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003215053,"about_ca_topic_score_gemma":0.00003731018,"domain_scores_codex":[0.9992825,0.000004740043,0.00024672,0.0001491696,0.00004851328,0.0002683749],"domain_scores_gemma":[0.9997562,0.00001493762,0.00002241152,0.0001681242,0.00001189706,0.00002650082],"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":[0.00007643495,0.0001092146,0.01086869,0.0006944649,0.0002104173,0.0001112499,0.0009737578,0.306718,0.5599502,0.0728097,0.00007814344,0.04739967],"study_design_scores_gemma":[0.0002841486,0.000102385,0.003408416,0.0002737697,0.0000194666,0.000048977,0.000104309,0.6138309,0.3743299,0.007085336,0.00005195181,0.0004603803],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8282154,0.003412816,0.1661809,0.00001344722,0.0002324213,0.0001024633,0.000004521935,0.001127502,0.0007104937],"genre_scores_gemma":[0.9716018,0.0008486508,0.02748544,0.000002449622,0.00002248172,0.00001158417,0.000003043787,0.00002299826,0.000001495475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3071129,"threshold_uncertainty_score":0.6170218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170972358873696,"score_gpt":0.183729385724899,"score_spread":0.172019662136162,"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."}}