{"id":"W2963460903","doi":"10.1103/physreve.100.012309","title":"Spectral properties of hyperbolic nanonetworks with tunable aggregation of simplexes","year":2019,"lang":"en","type":"article","venue":"Physical review. E","topic":"Supramolecular Self-Assembly in Materials","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja; Javna Agencija za Raziskovalno Dejavnost RS","keywords":"Simplex; Dimension (graph theory); Substructure; Topology (electrical circuits); Hyperbolic geometry; Spectral properties; Tetrahedron; Mathematics; Range (aeronautics); Computer science; Statistical physics; Pure mathematics; Physics; Combinatorics; Materials science; Geometry; Differential geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003092648,0.0001519721,0.0006233525,0.00002297495,0.00001981033,0.00001956138,0.0002536328,0.00002613857,0.0001808873],"category_scores_gemma":[0.00008272526,0.0001001869,0.00008840593,0.0001959965,0.00009080986,0.0001820451,0.000062299,0.00004885865,0.0001840346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001887095,"about_ca_system_score_gemma":0.00005835972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005673439,"about_ca_topic_score_gemma":0.000002008162,"domain_scores_codex":[0.998674,0.0001490257,0.0003446741,0.0002391637,0.0003589474,0.0002341991],"domain_scores_gemma":[0.9990687,0.00004965754,0.0002919233,0.0004218162,0.0001261001,0.00004180967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003766796,0.0001040727,0.0003063511,0.001568538,0.00001148943,6.857593e-7,0.00007218899,0.00008486821,0.9961669,0.001350438,0.00005691034,0.00023982],"study_design_scores_gemma":[0.0001725295,0.0001913377,0.0003628966,0.00185523,0.00005756305,0.000003561043,0.00001248773,0.0001338415,0.9962847,0.0005796799,0.0002145501,0.0001316626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995234,0.003507624,0.00003509729,0.00005078099,0.00009958283,0.0005648022,0.000004646659,0.00003050654,0.0004729611],"genre_scores_gemma":[0.9985153,0.0006169464,0.0006159064,0.0000811638,0.00008492002,0.00003065646,0.000003614066,0.00002164863,0.00002986564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00328128,"threshold_uncertainty_score":0.4085503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227543524544396,"score_gpt":0.2631301157846065,"score_spread":0.2508546805391626,"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."}}