{"id":"W4402748318","doi":"10.1016/j.apsusc.2024.161300","title":"Innovative ice mitigation: Exploring the potential of choline-based deep eutectic solvents and ionic liquids synergies","year":2024,"lang":"en","type":"article","venue":"Applied Surface Science","topic":"Ionic liquids properties and applications","field":"Chemical Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Chicoutimi","keywords":"Ionic liquid; Eutectic system; Choline chloride; Deep eutectic solvent; Chemical engineering; Process (computing); Chemistry; Materials science; Nanotechnology; Environmental science; Process engineering; Engineering; Computer science; Metallurgy; Organic chemistry; Catalysis","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":[0.0004128542,0.00011921,0.0001113958,0.0000583844,0.0002751622,0.00009820968,0.0003273526,0.00003069516,0.00001657385],"category_scores_gemma":[0.00004283729,0.00008418997,0.00002707947,0.001418571,0.0005446945,0.0002871936,0.0001372998,0.0001920138,0.00001490093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005956354,"about_ca_system_score_gemma":0.0001378396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002396387,"about_ca_topic_score_gemma":8.177651e-7,"domain_scores_codex":[0.9988622,0.000007419168,0.0002286958,0.0003200594,0.0003290928,0.0002525037],"domain_scores_gemma":[0.9994301,0.0001008598,0.00003929424,0.0002556474,0.0001257445,0.00004842014],"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":[0.000008625587,0.00001257604,0.000003257666,0.00006185057,0.00001044558,5.047864e-7,0.0003930686,0.05942239,0.888295,0.04945417,0.00000726521,0.00233083],"study_design_scores_gemma":[0.0001423957,0.00002301546,0.0001241827,0.00007152333,0.00001533006,0.000002777134,0.000569977,0.2832751,0.7146354,0.0004507378,0.0005457047,0.0001438664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9736687,0.0003824536,0.0237481,0.0008548078,0.0001918727,0.0002037159,0.000004283027,0.000123448,0.0008226405],"genre_scores_gemma":[0.9980931,0.00002620915,0.001574396,0.00007267462,0.00005093462,0.00007652844,0.000002567437,0.00001431888,0.00008926275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2238527,"threshold_uncertainty_score":0.3433168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770860216380105,"score_gpt":0.2418067618984818,"score_spread":0.2240981597346808,"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."}}