{"id":"W4303953721","doi":"10.1002/cjce.24709","title":"Solubility correlation by model with partial molar volume","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Crystallization and Solubility Studies","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Solubility; Mole fraction; Thermodynamics; Solvent; Partial molar property; Molar; Volume fraction; Correlation coefficient; Volume (thermodynamics); Absolute deviation; Chemistry; Hildebrand solubility parameter; Molar volume; Binary number; Work (physics); Materials science; Physical chemistry; Organic chemistry; Mathematics; Statistics; Physics; Orthodontics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00213959,0.001195293,0.001222542,0.001233092,0.0004242712,0.001035749,0.002805426,0.001371016,0.002133167],"category_scores_gemma":[0.005234924,0.0007009743,0.001767823,0.001705809,0.0009088148,0.002594533,0.0009807639,0.00152947,0.001372839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286893,"about_ca_system_score_gemma":0.001525175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00469422,"about_ca_topic_score_gemma":0.002167674,"domain_scores_codex":[0.9984614,0.0005093194,0.00008211708,0.0002896211,0.0005427072,0.0001148034],"domain_scores_gemma":[0.9981461,0.0009714278,0.0001877835,0.0002965489,0.0003592463,0.00003900134],"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":[0.00008509562,0.00007222688,0.0007865297,0.000187499,0.0000572149,0.0001265447,0.0001023498,0.9459503,0.009535412,0.0245966,0.001588914,0.01691132],"study_design_scores_gemma":[0.000004636646,0.00001940626,0.00008595161,0.000004202814,0.000006919317,0.00002433672,0.000003782365,0.9936134,0.001762055,0.003194196,0.00127072,0.0000104269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05487305,0.002242425,0.9314588,0.0005969513,0.0002623528,0.0002646572,0.0007987512,0.001452692,0.008050424],"genre_scores_gemma":[0.8724532,0.002774516,0.1045715,0.0004742253,0.0001855301,0.001443788,0.001746259,0.0005773829,0.01577362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00469422,"threshold_uncertainty_score":0.01131535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00862833998900899,"score_gpt":0.181571879542291,"score_spread":0.172943539553282,"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."}}