{"id":"W3045316679","doi":"10.1088/1361-6528/aba86d","title":"Genetic Algorithm Optimization of Core-Shell Nanowire Betavoltaic Generators","year":2020,"lang":"en","type":"article","venue":"Nanotechnology","topic":"Advanced Energy Technologies and Civil Engineering Innovations","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanowire; Materials science; Gallium arsenide; Nickel; Shell (structure); Gallium; Doping; Deposition (geology); Optoelectronics; Gallium phosphide; Nanotechnology; Composite material","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":[0.0005730868,0.0004280468,0.00045024,0.0004589925,0.0002201042,0.0005051331,0.0004651188,0.0007054376,0.00122208],"category_scores_gemma":[0.001227803,0.0003286927,0.0003136724,0.0003138934,0.0003433705,0.0001921328,0.0002552492,0.0003155855,0.000147714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009063234,"about_ca_system_score_gemma":0.0007297356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003744898,"about_ca_topic_score_gemma":0.003598209,"domain_scores_codex":[0.9998872,0.00003678628,0.000002993113,0.00001695649,0.00003135172,0.00002465791],"domain_scores_gemma":[0.9995309,0.0002973916,0.00004264546,0.00001218234,0.00009677331,0.00002015617],"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":[0.00002147358,0.00001682551,0.0002138349,0.00001217677,0.000007833443,0.00002115381,0.00001170566,0.9921634,0.00120327,0.001113434,0.0001382024,0.005076592],"study_design_scores_gemma":[0.000008513392,0.00001714128,0.00005924345,0.000001748764,0.000001805697,0.000001890316,0.00000402023,0.9992641,0.0003263777,0.0002006624,0.0001132932,0.000001173613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5435477,0.0003794452,0.4341307,0.00039784,0.00007156534,0.0001762416,0.0001417586,0.000421642,0.02073316],"genre_scores_gemma":[0.8953317,0.00009620108,0.1003404,0.00005627055,0.000008642399,0.0001921113,0.0001150655,0.00005098152,0.003808595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003744898,"threshold_uncertainty_score":0.007446229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403042060516759,"score_gpt":0.2140667865616982,"score_spread":0.2000363659565306,"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."}}