{"id":"W2566127830","doi":"10.1016/j.fuel.2016.12.070","title":"Pore-scale analysis of condensing solvent bitumen extraction","year":2016,"lang":"en","type":"article","venue":"Fuel","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Suncor Energy (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Suncor Energy Incorporated","keywords":"Asphaltene; Butane; Propane; Micromodel; Asphalt; Solvent; Chemical engineering; Residual oil; Hydrocarbon; Chemistry; Dissolution; Oil sands; Materials science; Organic chemistry; Catalysis; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001391593,0.0001761007,0.0002541183,0.0003037126,0.0002473729,0.0002906806,0.000211516,0.0002636611,0.001349417],"category_scores_gemma":[0.0003093283,0.00007611721,0.0002021711,0.0002813656,0.0003408673,0.0003789913,0.0002053945,0.0004873036,0.0004495678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295154,"about_ca_system_score_gemma":0.0002912132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804768,"about_ca_topic_score_gemma":0.003472622,"domain_scores_codex":[0.9998364,0.000009313523,0.000006068562,0.00002629884,0.00009567875,0.00002611068],"domain_scores_gemma":[0.9998763,0.00004346667,0.00001688752,0.000009995923,0.00004236056,0.00001097305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003256569,0.00001606596,0.000229686,0.00001500951,0.000002236603,0.00001381375,0.00001432962,0.00008437275,0.9982004,0.00006151868,0.00001511431,0.001314796],"study_design_scores_gemma":[0.00000164481,0.00002806747,0.001835598,0.000001262332,0.000003465948,0.00001730718,0.00001970256,0.0008872162,0.996832,0.00001787025,0.0003537311,0.000002148463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852794,0.0002805491,0.01185889,0.00003750763,0.00001704157,0.00004526192,0.0004947741,0.000136762,0.001849789],"genre_scores_gemma":[0.9914706,0.0003639204,0.005367721,0.00002701713,0.000005593744,0.00003094075,0.0003512484,0.00003738123,0.002345522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001804768,"threshold_uncertainty_score":0.004514277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008160924944920996,"score_gpt":0.2409244230798256,"score_spread":0.2327634981349046,"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."}}