{"id":"W2779087066","doi":"10.1063/1.4996202","title":"High temperature characterization of piezoelectric lithium niobate using electrochemical impedance spectroscopy resonance method","year":2017,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lithium niobate; Materials science; Piezoelectricity; Curie temperature; Dielectric spectroscopy; Ceramic; Atmospheric temperature range; Lithium (medication); Optoelectronics; Composite material; Electrochemistry; Condensed matter physics; Chemistry; Electrode","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":[],"consensus_categories":[],"category_scores_codex":[0.0001687091,0.0002011366,0.0004599517,0.0000725812,0.00009754967,0.00005553812,0.0004970756,0.0001753873,0.000002130117],"category_scores_gemma":[0.00004683562,0.0001863986,0.00009186139,0.000206128,0.0000693588,0.0002004514,0.00004590142,0.0006419454,9.515102e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001516077,"about_ca_system_score_gemma":0.0000645318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.644125e-7,"about_ca_topic_score_gemma":6.601516e-8,"domain_scores_codex":[0.9988806,0.000009370242,0.0004069668,0.0001330204,0.0002943954,0.0002756892],"domain_scores_gemma":[0.9987822,0.00004105792,0.0006044229,0.0003803863,0.0001463069,0.00004558851],"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":[0.0000618292,0.00002373747,0.00003591365,0.00006056431,0.00004988101,0.000004152331,0.00003565694,0.003527844,0.9881749,0.001404868,0.00004462655,0.006576034],"study_design_scores_gemma":[0.0003079146,0.00004916921,0.0006040445,0.00006684712,0.00005076931,0.0000200803,0.00001001086,0.03560073,0.9584238,0.004626521,0.00008057912,0.0001595376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.849008,0.0001726463,0.1503579,0.00001634967,0.0001680717,0.00009244658,0.000008805011,0.00005827846,0.0001175244],"genre_scores_gemma":[0.9263346,0.0003149454,0.07282449,0.00001050085,0.0004629849,0.000002193412,0.000002405791,0.00004241624,0.000005520281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07753341,"threshold_uncertainty_score":0.7601115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008319220423535662,"score_gpt":0.2472640087631532,"score_spread":0.2389447883396175,"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."}}