{"id":"W1909612126","doi":"10.1109/iwmpi.2015.7107089","title":"A novel scanner architecture for MPI","year":2015,"lang":"en","type":"article","venue":"","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Scanner; Computer science; Scaling; Architecture; Field (mathematics); Image quality; Quality (philosophy); Point (geometry); Image (mathematics); Artificial intelligence; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.00003036162,0.00004152299,0.00003907735,0.00002021258,0.00001127414,0.00001622141,0.00005013336,0.00001677515,0.00003822029],"category_scores_gemma":[0.00001288894,0.00003613406,0.00001406161,0.00005893316,0.000007975085,0.00002206686,0.000006045119,0.00001723195,0.00003293125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007249701,"about_ca_system_score_gemma":0.000006212349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001688752,"about_ca_topic_score_gemma":0.00000546225,"domain_scores_codex":[0.9997734,8.347095e-7,0.00006251608,0.00005024922,0.00003787249,0.00007508885],"domain_scores_gemma":[0.9998106,0.00001102563,0.000004506112,0.0000860704,0.00002616947,0.00006165104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000169521,0.00008351552,0.00007490846,0.00003879166,0.00001848406,1.508981e-7,0.0004301113,0.04241487,0.7811661,0.02331123,0.07519886,0.07724603],"study_design_scores_gemma":[0.001125098,0.00003493308,0.0005267113,0.00000478828,0.000008940557,0.0000073087,0.00008112555,0.09300282,0.07840906,0.001993346,0.8246019,0.0002039143],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09900712,0.00003946918,0.8867068,0.001570094,0.0001115649,0.0002531365,0.00002005283,0.0004221266,0.01186967],"genre_scores_gemma":[0.9533771,0.000001467921,0.04483415,0.0002231261,0.00009098335,0.00009485116,0.00001746937,0.00001639344,0.001344484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8543699,"threshold_uncertainty_score":0.1473504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02416880442579099,"score_gpt":0.2274264374401875,"score_spread":0.2032576330143964,"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."}}