{"id":"W4411865334","doi":"10.2139/ssrn.5334423","title":"Numerical Investigation of Gas Distribution Layer (Gdl) Influence on Methane Removal Efficiency in Engineered Methane Oxidation Biosystems (Mobs)","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Methane; Methane gas; Layer (electronics); Anaerobic oxidation of methane; Chemical engineering; Chemistry; Materials science; Environmental science; Engineering; Nanotechnology; Organic chemistry","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":[0.0002060536,0.000293348,0.000419907,0.0003074644,0.0004311966,0.0006210489,0.0004693267,0.001072645,0.00180656],"category_scores_gemma":[0.001192019,0.0001969928,0.0004664039,0.0003601809,0.0004492388,0.0003434198,0.0004017329,0.0004993158,0.0001083581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005849933,"about_ca_system_score_gemma":0.0004059658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01556834,"about_ca_topic_score_gemma":0.006243155,"domain_scores_codex":[0.9999188,0.00001370566,0.000003652238,0.00001674679,0.00001778855,0.00002924833],"domain_scores_gemma":[0.9993398,0.0004549441,0.0000624709,0.00003233489,0.00007845657,0.00003207035],"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":[0.0001871752,0.000153473,0.007191836,0.0001505951,0.00003341094,0.000239121,0.0000664262,0.9623403,0.02332385,0.001503006,0.000351938,0.004458825],"study_design_scores_gemma":[0.00001830627,0.00006717224,0.001692716,0.000007311321,0.00001180477,0.00001416836,0.00005642807,0.9939221,0.003902297,0.000147434,0.0001515397,0.000008664178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916444,0.000168036,0.003458811,0.0001706418,0.00003355814,0.00001112051,0.0002388519,0.00007277372,0.004201638],"genre_scores_gemma":[0.9982835,0.00005053715,0.001127118,0.00001434885,0.000003376208,0.00000773169,0.00005752489,0.000007905506,0.000447949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01556834,"threshold_uncertainty_score":0.03095543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00651436810563477,"score_gpt":0.2218629640414415,"score_spread":0.2153485959358067,"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."}}