{"id":"W2793587594","doi":"10.1039/c7nr06869g","title":"Ultraviolet sensing using a TiO<sub>2</sub>nanotube integrated high resolution planar microwave resonator device","year":2018,"lang":"en","type":"article","venue":"Nanoscale","topic":"Gas Sensing Nanomaterials and Sensors","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Alberta Innovates - Technology Futures","keywords":"Ultraviolet; Planar; Materials science; Microwave; Resonator; Optoelectronics; Limit (mathematics); Detection limit; Resolution (logic); High resolution; Nanotube; Optics; Carbon nanotube; Nanotechnology; Physics; Computer science; Remote sensing; Telecommunications; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000203585,0.0003427035,0.0003721358,0.0001843876,0.0002401699,0.0001089411,0.0001220561,0.0003182172,0.00001206395],"category_scores_gemma":[0.00006017283,0.0003457477,0.00008358072,0.0004034181,0.0001428937,0.0001389792,0.00002433905,0.0001984069,0.0001714527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562751,"about_ca_system_score_gemma":0.00004708466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000271081,"about_ca_topic_score_gemma":0.0002433742,"domain_scores_codex":[0.9982184,0.0001034646,0.0004513547,0.0003860093,0.0002355807,0.0006052138],"domain_scores_gemma":[0.9991661,0.00005682631,0.00008054393,0.0003556183,0.0001984202,0.0001424592],"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":[0.00004447195,0.00001515196,0.0000425631,0.00003213869,0.00003059836,0.00003458584,0.0002464697,0.0003144036,0.9954486,0.00003163852,0.001756145,0.002003192],"study_design_scores_gemma":[0.0004324816,0.00006416166,0.001031728,0.0002304279,0.00004797432,0.0001242475,0.00008315112,0.02357708,0.9707482,0.00009598621,0.003157078,0.0004074263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943655,0.0001413241,0.002755496,0.00005154369,0.001643686,0.0002073027,0.00005795278,0.0005380705,0.000239156],"genre_scores_gemma":[0.9905476,0.00003314958,0.008542129,0.0001323284,0.0005441572,0.000001110147,0.00006253213,0.0001027712,0.00003421314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02470038,"threshold_uncertainty_score":0.9998994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322031676892976,"score_gpt":0.209451523462592,"score_spread":0.1962312066936622,"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."}}