{"id":"W2404070135","doi":"10.1021/acs.jpca.5b02809","title":"Dispersion Corrections Improve the Accuracy of Both Noncovalent and Covalent Interactions Energies Predicted by a Density-Functional Theory Approximation","year":2015,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"Free Radicals and Antioxidants","field":"Chemistry","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Western Canada Research Grid; Compute Canada","keywords":"Density functional theory; Non-covalent interactions; Pairwise comparison; London dispersion force; Dispersion (optics); Dissociation (chemistry); Covalent bond; Basis set; Bond-dissociation energy; Work (physics); Computational chemistry; Molecule; Physics; Chemistry; Thermodynamics; Statistical physics; Materials science; Chemical physics; Quantum mechanics; Physical chemistry; Computer science; van der Waals force","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":[0.001053919,0.00163535,0.0006973137,0.0008694855,0.0007428876,0.0006291242,0.001644708,0.0009700648,0.002161742],"category_scores_gemma":[0.002986329,0.000378646,0.0007758467,0.0008305942,0.0004965476,0.001032756,0.0009575849,0.001678518,0.0007076534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006608044,"about_ca_system_score_gemma":0.001391264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007135415,"about_ca_topic_score_gemma":0.008018962,"domain_scores_codex":[0.9995002,0.0001396931,0.00003181927,0.00004682896,0.000227673,0.00005381675],"domain_scores_gemma":[0.9988368,0.0005852556,0.00008051975,0.0002727967,0.0001815913,0.00004306559],"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":[0.0001245412,0.0002329396,0.003605849,0.0003982435,0.0002154991,0.0003180083,0.0001754705,0.8201044,0.02704563,0.06072717,0.002661849,0.08439045],"study_design_scores_gemma":[0.00001901371,0.00006183953,0.0005385523,0.00002530354,0.00002208146,0.00003893941,0.00002326751,0.9791199,0.009574295,0.009257928,0.001295204,0.00002360137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3137091,0.002473904,0.646889,0.001109097,0.0004383379,0.0001407105,0.0004944287,0.003678449,0.03106701],"genre_scores_gemma":[0.8849519,0.001176623,0.1089604,0.0001734983,0.00005639814,0.0001230775,0.0003599603,0.0004664665,0.003731634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007135415,"threshold_uncertainty_score":0.01418775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234723562428397,"score_gpt":0.2386688525571236,"score_spread":0.2263216169328396,"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."}}