{"id":"W2657318927","doi":"10.1021/acs.jpcc.7b03684","title":"Structural Characterization of AgI–AgPO<sub>3</sub>–Ag<sub>2</sub>WO<sub>4</sub> Superionic Conducting Glasses by Advanced Solid-State NMR Techniques","year":2017,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Glass properties and applications","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Fundação de Amparo à Pesquisa do Estado de São Paulo; Canada Foundation for Innovation","keywords":"Tungstate; Silver iodide; Materials science; Raman spectroscopy; Analytical Chemistry (journal); Ion; Quenching (fluorescence); Iodide; Ionic bonding; Tungsten; Crystallography; Inorganic chemistry; Chemistry; Fluorescence; Nanotechnology","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":[0.00005628272,0.0001985114,0.0001034663,0.0002788959,0.0001206323,0.0001760122,0.0001335845,0.0001869812,0.0006615073],"category_scores_gemma":[0.0001338682,0.0001514866,0.00009631856,0.0001664919,0.0002933029,0.0001634912,0.0001287583,0.0001771926,0.0001591741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001440619,"about_ca_system_score_gemma":0.0001763109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001823997,"about_ca_topic_score_gemma":0.002538495,"domain_scores_codex":[0.9999543,0.00000344022,0.000003170531,0.00001112164,0.00001825313,0.000009607422],"domain_scores_gemma":[0.9999218,0.00001230698,0.00002609984,0.000005507216,0.00001790082,0.00001634888],"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":[0.00001854543,0.000001839414,0.000250695,0.00001180967,0.000001107835,0.00001824914,0.00001730393,0.00005225607,0.9991979,0.00001997203,0.000005613879,0.000404672],"study_design_scores_gemma":[0.000007720205,0.0002542323,0.02433423,0.000005175306,0.00002900251,0.0002107491,0.0001144872,0.002371014,0.9713391,0.00008250828,0.00124098,0.00001078268],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978168,0.0001182212,0.00120934,0.00001644597,0.000003662354,0.00001043727,0.0001811913,0.00002863701,0.0006151801],"genre_scores_gemma":[0.9974643,0.0001504641,0.001304725,0.00001239301,0.000003585934,0.00001048443,0.0003117021,0.00001893259,0.0007233918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001823997,"threshold_uncertainty_score":0.003626823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01624895985242869,"score_gpt":0.26301215335666,"score_spread":0.2467631935042313,"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."}}