{"id":"W4408234780","doi":"10.1021/acssusresmgt.4c00376","title":"Pore-Scale Analysis of Green Solvents for Solvent-Based Bitumen Recovery","year":2025,"lang":"en","type":"article","venue":"ACS Sustainable Resource Management","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canada First Research Excellence Fund","keywords":"Asphalt; Solvent; Scale (ratio); Chemistry; Chromatography; Chemical engineering; Environmental science; Materials science; Organic chemistry; Engineering; Composite material; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.000545991,0.0001902897,0.0003360771,0.001493695,0.00009584997,0.00003021362,0.0002977452,0.00008662979,0.00002117839],"category_scores_gemma":[0.00001234824,0.0002073219,0.0001637987,0.003252806,0.00005042141,0.00007864492,0.0001370876,0.00008523188,9.787883e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003846476,"about_ca_system_score_gemma":0.00002683748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004623995,"about_ca_topic_score_gemma":0.000001108112,"domain_scores_codex":[0.9986607,0.00001502393,0.0004777752,0.000256486,0.0001778645,0.0004121484],"domain_scores_gemma":[0.9991443,0.00003757914,0.00009618076,0.0004678983,0.0002323657,0.00002168097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005517775,0.0007043296,0.003110784,0.01447572,0.01632933,0.00009234228,0.0007224109,0.09147448,0.0207922,0.3773752,0.3014197,0.1729517],"study_design_scores_gemma":[0.00150347,0.0001561187,0.001424971,0.0001738222,0.00234824,2.607772e-7,0.005782233,0.02165041,0.185462,0.007796844,0.7731254,0.0005762089],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01940498,0.0002745175,0.9298924,0.0002864518,0.00005581348,0.001137952,0.00003273154,0.0002939316,0.04862128],"genre_scores_gemma":[0.9485859,0.00002132172,0.004185873,0.0004680863,0.00002553275,0.000451357,0.0007557314,0.0000499811,0.04545616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.929181,"threshold_uncertainty_score":0.845434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005819220987115167,"score_gpt":0.2311748718304735,"score_spread":0.2253556508433583,"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."}}