{"id":"W2334521826","doi":"10.1021/ct500832g","title":"Unraveling Interactions in Molecular Crystals Using Dispersion Corrected Density Functional Theory: The Case of the Epoxydihydroarsanthrene Molecules","year":2014,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Crystallography and molecular interactions","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology","funders":"Ministerio de Economía y Competitividad; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministry of Higher Education, Malaysia","keywords":"Pnictogen; Chalcogen; Supramolecular chemistry; Non-covalent interactions; Chemical physics; Density functional theory; Crystal (programming language); Hydrogen bond; Chemistry; Crystallography; Computational chemistry; Materials science; Crystal structure; Molecule; Physics; Condensed matter physics; Computer science; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003306416,0.0002909992,0.0005683857,0.0003803901,0.000464495,0.0005154804,0.0006232609,0.0006506181,0.0007731358],"category_scores_gemma":[0.0003866308,0.0002332317,0.0002665594,0.0003757428,0.0007089158,0.0004698544,0.0002491957,0.0006483155,0.00008787024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000556074,"about_ca_system_score_gemma":0.0005686242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004783846,"about_ca_topic_score_gemma":0.004572599,"domain_scores_codex":[0.9998977,0.00003057955,0.00000434264,0.000007866804,0.00004195319,0.00001753673],"domain_scores_gemma":[0.9998229,0.00009680232,0.00001899208,0.00002358816,0.00002569604,0.00001204113],"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":[0.00009884419,0.0001239274,0.00204913,0.0002121703,0.00004081093,0.0003957589,0.0001511361,0.8991297,0.03237989,0.05279743,0.0006346089,0.01198647],"study_design_scores_gemma":[0.00001236873,0.00001875293,0.0002898644,0.000006641494,0.000004072463,0.0000136362,0.00003350142,0.9918886,0.002468471,0.004999093,0.0002594259,0.00000566007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9211585,0.0007705052,0.07023779,0.0004477165,0.00003315022,0.00004619263,0.0002537403,0.0001316974,0.006920706],"genre_scores_gemma":[0.9777942,0.0004569803,0.02081764,0.0000614965,0.0000118836,0.00006036073,0.0001757064,0.00002964285,0.0005921403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004783846,"threshold_uncertainty_score":0.009512007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221617185973116,"score_gpt":0.2643012847703823,"score_spread":0.2520851129106512,"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."}}