{"id":"W4403640724","doi":"10.1063/5.0232574","title":"A modular, low-field magnetic resonance design with pre-polarization for characterizing flows","year":2024,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Physics; Modular design; Magnetic field; Polarization (electrochemistry); Nuclear magnetic resonance; Computational physics; Quantum mechanics","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":[0.0007271424,0.0005896807,0.0004238894,0.0005688908,0.0002358091,0.0004380379,0.0007973015,0.0005876351,0.001099737],"category_scores_gemma":[0.0007416751,0.000434953,0.0003203578,0.0003150837,0.0005295093,0.0006460179,0.0003494542,0.0007344784,0.0007875942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294471,"about_ca_system_score_gemma":0.0005350342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001774681,"about_ca_topic_score_gemma":0.0003289798,"domain_scores_codex":[0.9995364,0.00006439178,0.0000267607,0.0001659906,0.0001541282,0.00005230165],"domain_scores_gemma":[0.9992505,0.0001228628,0.0002419912,0.00008755404,0.0001972729,0.00009991016],"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":[0.0001192628,0.00003728442,0.0002930217,0.00007201359,0.000006266685,0.00003426668,0.00003008938,0.0003238398,0.9912709,0.0005008755,0.0001345146,0.007177643],"study_design_scores_gemma":[0.00005267311,0.000840144,0.002658952,0.000009358451,0.00002727328,0.0003350938,0.0000171044,0.005018327,0.9842886,0.0002105504,0.006496277,0.00004560529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4236925,0.0004568265,0.5689389,0.0004708455,0.0002155589,0.0004681072,0.0004753643,0.001963443,0.003318513],"genre_scores_gemma":[0.5182369,0.0003006893,0.4764244,0.0003478994,0.0001110655,0.0004894986,0.0003405878,0.0001614271,0.003587526],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001099737,"threshold_uncertainty_score":0.003845572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055508585879303,"score_gpt":0.2828057396214921,"score_spread":0.272250653762699,"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."}}