{"id":"W2742990248","doi":"10.1109/intmag.2017.8007938","title":"Magnetic resonance spectroscopy with torsional optomechanics","year":2017,"lang":"en","type":"article","venue":"2017 IEEE International Magnetics Conference (INTERMAG)","topic":"Mechanical and Optical Resonators","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"","keywords":"Optomechanics; Spectroscopy; Resonance (particle physics); Nuclear magnetic resonance; Physics; Optics; Optoelectronics; Materials science; Atomic physics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":false,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001416806,0.0003488545,0.0003064257,0.00007613841,0.0003554746,0.0006609923,0.001775023,0.00008815056,0.008858011],"category_scores_gemma":[0.0000571104,0.0002891789,0.0001384019,0.0000383667,0.0002919242,0.0003401313,0.0003108445,0.0004189043,0.0005983231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004587729,"about_ca_system_score_gemma":0.0001380669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001263379,"about_ca_topic_score_gemma":0.00002906692,"domain_scores_codex":[0.9978347,0.00003050927,0.0003745663,0.0005799955,0.0006858698,0.0004943957],"domain_scores_gemma":[0.9981416,0.00008063234,0.0002709416,0.0008282576,0.000382772,0.0002957874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006168265,0.0006754826,0.01991107,0.0000277843,0.0001342959,0.0001123019,0.000172954,0.000009989252,0.01794857,0.7598748,0.007880578,0.1926354],"study_design_scores_gemma":[0.01164805,0.004824267,0.1015536,0.001689727,0.0003585976,0.0001123961,0.0005298448,0.1511405,0.1259501,0.1810815,0.4163333,0.004778055],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5449516,0.0002043385,0.03119791,0.004398194,0.004451155,0.000659322,0.0004888499,0.000120755,0.4135279],"genre_scores_gemma":[0.9813817,0.00004294796,0.004368642,0.000157538,0.0006832437,0.00004792102,0.00003063096,0.00003176441,0.01325564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5787932,"threshold_uncertainty_score":0.999956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254075214940255,"score_gpt":0.2953190142913399,"score_spread":0.2699114927973144,"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."}}