{"id":"W2316967158","doi":"10.2118/179706-ms","title":"Characterization of Mixed Wettability using Surface Energy Distribution","year":2016,"lang":"en","type":"article","venue":"SPE Improved Oil Recovery Conference","topic":"Adsorption, diffusion, and thermodynamic properties of materials","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CMG Reservoir Simulation Foundation","keywords":"Wetting; Inverse gas chromatography; Dolomite; Mineralogy; Surface energy; Calcite; Characterization (materials science); Contact angle; Petroleum reservoir; Geology; Materials science; Petroleum engineering; Composite material; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002013295,0.0002190205,0.000323437,0.0000193007,0.00007593646,0.00003977005,0.0002470548,0.0001871158,0.001504783],"category_scores_gemma":[0.0001742932,0.0001623126,0.00009270418,0.0000636084,0.0001491408,0.0003814879,0.0001036198,0.00005102461,0.00001008912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001864162,"about_ca_system_score_gemma":0.0001982799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004836798,"about_ca_topic_score_gemma":0.00005911496,"domain_scores_codex":[0.9985867,0.00006765474,0.0005017644,0.0003774596,0.0001835119,0.0002829814],"domain_scores_gemma":[0.9987,0.00006759411,0.0004073071,0.0004625618,0.0002837122,0.00007881308],"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":[0.0002390255,0.00007184441,0.0003699908,0.0001086023,0.00002188052,3.454326e-7,0.00001763927,0.000002453089,0.9387773,0.0004559009,0.00000251158,0.05993247],"study_design_scores_gemma":[0.0005993611,0.0000360082,0.001298605,0.0002215506,0.00002467437,0.000003357301,0.0000156256,0.002411918,0.9928515,0.001454417,0.0008176344,0.0002653305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738331,0.00002157533,0.02393923,0.00008077136,0.0004133971,0.00003347501,0.0008196894,0.00007313713,0.0007855909],"genre_scores_gemma":[0.9962851,0.0004523782,0.0001377968,0.00001013445,0.00009968044,0.000005859919,0.0002796823,0.00002302834,0.002706282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05966714,"threshold_uncertainty_score":0.999408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01570021650833986,"score_gpt":0.2104854258205462,"score_spread":0.1947852093122063,"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."}}