{"id":"W6990124524","doi":"","title":"Computational Modeling of Dynamic Electron Paramagnetic Resonance Spectra","year":2019,"lang":"en","type":"dissertation","venue":"ResearchWorks at the University of Washington (University of Washington)","topic":"Electron Spin Resonance Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canarie","keywords":"Spectral line; Resonance (particle physics); Electron paramagnetic resonance; Electron nuclear double resonance; Pulsed EPR; Ferromagnetic resonance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006392121,0.0003533966,0.000681181,0.0002784951,0.0005453957,0.0000133577,0.001677951,0.0004951042,0.0001447329],"category_scores_gemma":[0.0001055955,0.0004156886,0.0004591215,0.0004376421,0.0006371004,0.00003376333,0.0006126729,0.0007583491,0.0000175987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002649686,"about_ca_system_score_gemma":0.0005876296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009755678,"about_ca_topic_score_gemma":0.004021423,"domain_scores_codex":[0.9972461,0.000271186,0.0002926328,0.0007082293,0.0008970773,0.0005847141],"domain_scores_gemma":[0.9977092,0.0001460694,0.0006039867,0.0007494846,0.0006921998,0.00009909335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.03464834,0.00180725,0.004530046,0.007089525,0.005473605,0.0001486178,0.03555753,0.3652243,0.4654516,0.005445844,0.03269359,0.04192971],"study_design_scores_gemma":[0.02228039,0.01324655,0.07623153,0.009991574,0.003140828,0.00007263735,0.1911959,0.5409225,0.06731293,0.004097671,0.0639805,0.007526985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863557,0.007285784,0.001361356,0.000361522,0.0000878176,0.0005592881,0.0001064745,0.00001873897,0.003863287],"genre_scores_gemma":[0.956661,0.007506312,0.001437684,0.000008594041,0.000025036,1.601776e-7,0.0009060633,0.00005059439,0.03340452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3981387,"threshold_uncertainty_score":0.9998295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008332344040320941,"score_gpt":0.2390754574377568,"score_spread":0.2307431133974359,"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."}}