{"id":"W3196805525","doi":"10.3390/physchem1020015","title":"Predicting 1,9-Decadiene−Water Partition Coefficients Using the 3D-RISM-KH Molecular Solvation Theory","year":2021,"lang":"en","type":"article","venue":"Physchem","topic":"Spectroscopy and Quantum Chemical Studies","field":"Physics and Astronomy","cited_by":1,"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; Partition coefficient; Partition (number theory); Liquid water; Closure (psychology); Thermodynamics; Chemistry; Statistical physics; Physics; Mathematics; Molecule; Chromatography; 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":[0.0001968032,0.0004541806,0.0005078471,0.0003978712,0.0003958661,0.0003639766,0.0005167789,0.00067129,0.001327183],"category_scores_gemma":[0.0004476686,0.0001791096,0.0005649374,0.0004315282,0.0002074172,0.0004987165,0.0003393879,0.0005008178,0.0002389836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004968006,"about_ca_system_score_gemma":0.001040508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006146056,"about_ca_topic_score_gemma":0.004769726,"domain_scores_codex":[0.9999462,0.00001094309,0.000002775403,0.000008860005,0.00001976223,0.00001147898],"domain_scores_gemma":[0.9998337,0.00008754985,0.00001867597,0.00001271973,0.00003059299,0.00001665417],"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":[0.00004918384,0.00006328202,0.001245427,0.0001310649,0.00002478223,0.0001406981,0.00003518851,0.9749005,0.01250302,0.005103951,0.0004164891,0.005386299],"study_design_scores_gemma":[0.000005817394,0.00001116817,0.0001423401,0.000001413931,0.00000248485,0.000006140649,0.000004293624,0.9981724,0.0012691,0.0003021532,0.0000796065,0.000003018873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8980773,0.0006424309,0.09300464,0.0002291659,0.00004873057,0.00008112097,0.0007145733,0.0004514399,0.006750598],"genre_scores_gemma":[0.9807576,0.0003200256,0.01698037,0.00003391282,0.00001181618,0.0001006508,0.000475198,0.0000666881,0.001253703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006146056,"threshold_uncertainty_score":0.01222056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406406080860747,"score_gpt":0.2654053987208826,"score_spread":0.2513413379122752,"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."}}