{"id":"W4399447570","doi":"10.48550/arxiv.2406.02895","title":"A computationally efficient queue-based algorithm for simulating volume-controlled drainage under the influence of gravity on volumetric images of porous materials","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canarie","keywords":"Volume (thermodynamics); Queue; Drainage; Algorithm; Computer science; Geology; Mathematical optimization; Mathematics; Physics; Thermodynamics; Biology; Computer network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005142434,0.0005077024,0.0005713745,0.0003930469,0.0005394907,0.0008365585,0.00181426,0.001106043,0.001760582],"category_scores_gemma":[0.001193041,0.0003461046,0.0005689356,0.000572846,0.0004291594,0.0008243725,0.0006322644,0.00084995,0.000267531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009475644,"about_ca_system_score_gemma":0.001734721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01351456,"about_ca_topic_score_gemma":0.01325321,"domain_scores_codex":[0.9998702,0.00002369904,0.000009287441,0.00002523081,0.00005123012,0.00002037494],"domain_scores_gemma":[0.9995753,0.0002211498,0.0000321905,0.00002134165,0.000110845,0.00003924223],"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":[0.000108694,0.00009676861,0.0008220728,0.00007565707,0.00003063098,0.0000880109,0.00008661766,0.9471378,0.01084408,0.008597532,0.001188928,0.0309232],"study_design_scores_gemma":[0.000009671514,0.000007178334,0.00002093313,7.717767e-7,0.000001349307,0.000003682411,0.00000176938,0.999006,0.0004857245,0.0003131986,0.000147448,0.000002353123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04102797,0.0001353223,0.9558898,0.0001509549,0.00007552469,0.0000879915,0.0001174379,0.0009175013,0.001597466],"genre_scores_gemma":[0.3697311,0.0001845238,0.6263771,0.0001159267,0.00003480937,0.0002537064,0.0003077663,0.0002307243,0.002764361],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01351456,"threshold_uncertainty_score":0.02687174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03107855065353396,"score_gpt":0.2325887611313316,"score_spread":0.2015102104777977,"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."}}