{"id":"W2302514230","doi":"10.1149/ma2013-01/8/465","title":"Understanding Invasion Mechanisms in Fibrous Gas Diffusion Media: Direct Comparison of Simulations with Tomographic Visualization","year":2013,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Diffusion; Tomographic reconstruction; Computed tomographic; Computer science; Tomography; Physics; Optics; Computed tomography; Artificial intelligence; Medicine; Radiology; Thermodynamics","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":[0.0001777984,0.0001416013,0.0002059634,0.0002290712,0.00008106465,0.00004576784,0.00006196228,0.00009184458,0.00002902671],"category_scores_gemma":[0.000154845,0.000135615,0.00002313298,0.0004538269,0.00002329363,0.000275844,0.000009451535,0.0001302384,0.000007175282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001050752,"about_ca_system_score_gemma":0.00001659136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001178113,"about_ca_topic_score_gemma":0.0004989477,"domain_scores_codex":[0.9988781,0.00004435664,0.0004499413,0.0001486945,0.0002659079,0.0002130385],"domain_scores_gemma":[0.9992699,0.0003564954,0.0001411637,0.0001103532,0.00006115818,0.00006090361],"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":[0.000008764114,0.00005021149,0.00620644,0.00005420287,0.00001007568,6.719817e-7,0.002346233,0.7230743,0.2678896,0.0002008127,0.0000639269,0.00009477314],"study_design_scores_gemma":[0.0007331105,0.0001393568,0.04028517,0.0004950151,0.00002474123,0.000001959929,0.001681996,0.6808873,0.2708992,0.004548997,0.000004643368,0.0002984208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755686,0.00004403145,0.0185752,0.00004316508,0.0001116592,0.0002931829,0.000003333765,0.0001775327,0.005183283],"genre_scores_gemma":[0.9976667,0.000014361,0.002159622,0.000008461963,0.00001711301,0.00001312987,0.00008665177,0.00002989782,0.000004050265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04218699,"threshold_uncertainty_score":0.553022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0346034316706248,"score_gpt":0.2502123459546869,"score_spread":0.2156089142840621,"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."}}