{"id":"W2035126047","doi":"10.1007/s00894-014-2566-0","title":"Computational study of interaction of alkali metals with C3N nanotubes","year":2015,"lang":"en","type":"article","venue":"Journal of Molecular Modeling","topic":"Graphene research and applications","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; Government of Ontario; Compute Canada","keywords":"Alkali metal; Adsorption; Graphene; Lithium (medication); Nanotube; Atom (system on chip); Carbon nanotube; Vacancy defect; Chemical physics; Materials science; Lithium atom; Metal; Fullerene; Work function; Density functional theory; Reactivity (psychology); Computational chemistry; Chemistry; Physical chemistry; Nanotechnology; Crystallography; Ion; Organic chemistry; Ionization","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":[0.0004277684,0.0006251578,0.001355365,0.0008843254,0.002204194,0.001197252,0.001892675,0.002260512,0.006828106],"category_scores_gemma":[0.001831353,0.0006160089,0.0007884544,0.001141654,0.001142789,0.0008744802,0.0008156652,0.001301807,0.0003377673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002021533,"about_ca_system_score_gemma":0.002039124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04636639,"about_ca_topic_score_gemma":0.03566157,"domain_scores_codex":[0.9997984,0.00004889995,0.000006566251,0.00002257372,0.00004841536,0.00007528053],"domain_scores_gemma":[0.9986111,0.0009977256,0.0000752725,0.00006692934,0.0001421939,0.0001068372],"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":[0.000252468,0.0002177957,0.002511674,0.0001271832,0.00007294721,0.0003027352,0.00007880767,0.9838821,0.001156044,0.008455756,0.001319103,0.001623455],"study_design_scores_gemma":[0.00005256799,0.00004474831,0.0005345211,0.000007344351,0.00001231904,0.00001469057,0.00006140155,0.9979373,0.0003827104,0.0007126703,0.0002324701,0.000007346907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697675,0.000285158,0.002224916,0.0009066779,0.0000688504,0.00003416256,0.0005364732,0.00008661822,0.02608966],"genre_scores_gemma":[0.9965394,0.0001035431,0.001301245,0.0001138806,0.00002246784,0.00004167828,0.000190566,0.00002748861,0.001659792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04636639,"threshold_uncertainty_score":0.09219301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05997368883948431,"score_gpt":0.335981474848338,"score_spread":0.2760077860088537,"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."}}