{"id":"W2809705601","doi":"10.1038/s41928-018-0107-z","title":"Perovskite nanowires find an edge","year":2018,"lang":"en","type":"article","venue":"Nature Electronics","topic":"Perovskite Materials and Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Nanowire; Enhanced Data Rates for GSM Evolution; Materials science; Perovskite (structure); Nanotechnology; Computer science; Crystallography; Chemistry; Artificial intelligence","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":[0.00007419439,0.0001321652,0.0001071786,0.00004091531,0.0001070609,0.00005845163,0.0002076674,0.0002509264,0.0001506941],"category_scores_gemma":[0.000009347239,0.0001249914,0.00003033502,0.0001582879,0.00003537746,0.0001113237,0.00001695708,0.0003440755,0.0001343978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006540469,"about_ca_system_score_gemma":0.00003190758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002241607,"about_ca_topic_score_gemma":0.00009409174,"domain_scores_codex":[0.9992706,0.00001046647,0.0001108288,0.0001683264,0.00009817274,0.0003416602],"domain_scores_gemma":[0.999561,0.00001131904,0.00001467286,0.0002954565,0.00005130258,0.00006627243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001168116,0.00005153524,0.00003633606,0.0000231522,0.00003485628,0.000001232573,0.0002311191,0.0001033751,0.9282851,0.02574932,0.0255274,0.01994484],"study_design_scores_gemma":[0.000175656,0.000138864,0.001989669,0.000008082451,0.00001442059,0.00001015079,0.000007991182,0.00447047,0.1956227,0.001878851,0.7954147,0.0002685027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871539,0.003201397,0.0004931381,0.0001258412,0.000430591,0.000118396,0.00002201908,0.0004321402,0.008022567],"genre_scores_gemma":[0.9978004,0.0001565831,0.0005413229,0.0001789434,0.0008682936,0.00002000079,0.00004292013,0.00003853847,0.0003530641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7698873,"threshold_uncertainty_score":0.5097002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003717000247021309,"score_gpt":0.2310676999740911,"score_spread":0.2273506997270698,"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."}}