{"id":"W2121135112","doi":"10.1002/mrm.22352","title":"Comparative SNR for high‐throughput mouse embryo MR microscopy","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Centre for Phenogenomics; Hospital for Sick Children; University of Toronto","funders":"British Heart Foundation","keywords":"Embryo; Throughput; Microscopy; Signal-to-noise ratio (imaging); Isotropy; High resolution; High-throughput screening; Biology; Computer science; Physics; Cell biology; Bioinformatics; Optics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002591935,0.0006563857,0.0006635759,0.0007383578,0.0004334653,0.0008147947,0.0007909574,0.0007857243,0.003140574],"category_scores_gemma":[0.005383672,0.0003280866,0.0004144173,0.0006364405,0.0004216384,0.001130236,0.0008252855,0.0007485286,0.000765254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008614545,"about_ca_system_score_gemma":0.0003946202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008683834,"about_ca_topic_score_gemma":0.001310801,"domain_scores_codex":[0.9985128,0.0004693171,0.00009260192,0.0002415397,0.0006038357,0.00007983798],"domain_scores_gemma":[0.9965229,0.001816228,0.0003286388,0.0004349923,0.0008032448,0.00009407547],"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":[0.0006514171,0.00007620265,0.001876531,0.0003978415,0.00006467495,0.0002216145,0.0002104799,0.005495407,0.9515193,0.002663744,0.001096171,0.03572664],"study_design_scores_gemma":[0.00004067212,0.001184333,0.01967909,0.0001177942,0.0001953545,0.001299391,0.000154131,0.04896146,0.9143639,0.002511187,0.01139421,0.0000985219],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3086882,0.004423348,0.6714579,0.0003296997,0.000210801,0.0002070284,0.001346449,0.00218595,0.01115063],"genre_scores_gemma":[0.6404456,0.002954573,0.3509603,0.0002127037,0.0000990785,0.0005101426,0.001620596,0.0006141124,0.002582885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003140574,"threshold_uncertainty_score":0.01370764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02720645550563325,"score_gpt":0.3742700704209731,"score_spread":0.3470636149153399,"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."}}