{"id":"W2752578785","doi":"10.1021/acs.jpcb.7b06375","title":"Predicting Accurate Solvation Free Energy in <i>n</i>-Octanol Using 3D-RISM-KH Molecular Theory of Solvation: Making Right Choices","year":2017,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Spectroscopy and Quantum Chemical Studies","field":"Physics and Astronomy","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solvation; Implicit solvation; Chemistry; Energy (signal processing); Octanol; Computational chemistry; Statistical physics; Thermodynamics; Physics; Molecule; Partition coefficient; Quantum mechanics; Organic chemistry","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":[0.0003971618,0.0003557813,0.0005158947,0.0005677319,0.0002860348,0.0004275856,0.0005657732,0.000493845,0.0004845141],"category_scores_gemma":[0.001093508,0.00017038,0.000450284,0.0004611425,0.0002708262,0.0006845027,0.0003134846,0.0004149998,0.0001733982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004333078,"about_ca_system_score_gemma":0.0004983541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002891159,"about_ca_topic_score_gemma":0.002691232,"domain_scores_codex":[0.9998949,0.00003506885,0.000007578785,0.00001524203,0.00003429908,0.00001288604],"domain_scores_gemma":[0.9996334,0.0002059358,0.00004218842,0.000036528,0.00006274605,0.0000190493],"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":[0.00007574489,0.0000435717,0.003376291,0.0001199764,0.00002262491,0.0001165767,0.00004608435,0.9657287,0.01222817,0.004760223,0.0007701538,0.0127118],"study_design_scores_gemma":[0.000006987285,0.00002371024,0.0003577717,0.000004334443,0.000003132707,0.000009149678,0.000009914733,0.9947073,0.003284864,0.001362436,0.0002249548,0.000005442108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8928146,0.001165487,0.101716,0.000409871,0.00004059856,0.00003075842,0.0005390888,0.0005189741,0.0027646],"genre_scores_gemma":[0.9752908,0.000405221,0.02330793,0.00005329951,0.00001533297,0.00004679651,0.0004278772,0.00008654319,0.0003661308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002891159,"threshold_uncertainty_score":0.005748689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151296750984742,"score_gpt":0.2839408916032775,"score_spread":0.2688112165048033,"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."}}