{"id":"W4390165890","doi":"10.1016/j.molliq.2023.123879","title":"An innovative method for calculating partial molar volume from a standard molecular trajectory","year":2023,"lang":"en","type":"article","venue":"Journal of Molecular Liquids","topic":"Phase Equilibria and Thermodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Trajectory; Partial molar property; Volume (thermodynamics); Molar; Molar volume; Chemistry; Materials science; Computational chemistry; Computer science; Thermodynamics; Physics; Medicine; Dentistry","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":[0.0007586299,0.0006979207,0.000736894,0.001205967,0.0006675746,0.000778633,0.002090216,0.0009252548,0.004630729],"category_scores_gemma":[0.002158314,0.0004228455,0.0005984084,0.00111668,0.000412805,0.00137354,0.0008294577,0.001499586,0.001784219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006672926,"about_ca_system_score_gemma":0.001448759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002421364,"about_ca_topic_score_gemma":0.003404489,"domain_scores_codex":[0.9995614,0.00006612691,0.00002360725,0.00007737981,0.0002508565,0.00002071693],"domain_scores_gemma":[0.9994841,0.000184507,0.00003658661,0.0001145359,0.0001522174,0.000028048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001839972,0.0001709921,0.001541463,0.0005186288,0.0001702397,0.0002688976,0.0002912015,0.1539018,0.1054919,0.2108573,0.007740584,0.5188629],"study_design_scores_gemma":[0.00003081056,0.00006587741,0.0004162453,0.00002521745,0.00003172692,0.000237436,0.00001620468,0.9411924,0.02569896,0.01660174,0.01562748,0.00005593999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002995905,0.00008375126,0.9945371,0.00003374653,0.00008189877,0.00005472982,0.00009232377,0.000816085,0.001304428],"genre_scores_gemma":[0.06504864,0.0002782783,0.9275756,0.00007091513,0.00006311137,0.0003760365,0.0003025867,0.0007861138,0.005498751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004630729,"threshold_uncertainty_score":0.01549131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01040581665397113,"score_gpt":0.2896222512580181,"score_spread":0.279216434604047,"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."}}