{"id":"W2037605578","doi":"10.1002/mrm.20683","title":"In vivo multiple‐mouse MRI at 7 Tesla","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Scanner; Radiofrequency coil; Magnetic resonance imaging; Imaging phantom; Image quality; Electromagnetic coil; Nuclear magnetic resonance; Contrast (vision); Isotropy; Radio frequency; Distortion (music); Physics; Nuclear medicine; Biomedical engineering; Optics; Computer science; Medicine; Image (mathematics); Radiology; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002512254,0.0001879977,0.0004110342,0.0002079435,0.00003703579,0.000002595332,0.0001474764,0.0001123876,0.001851683],"category_scores_gemma":[0.0002269559,0.0001543258,0.00003416916,0.0005006648,0.0002204511,0.00006365711,0.00006462527,0.0003081649,0.00005822035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002496917,"about_ca_system_score_gemma":0.00002938213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002085097,"about_ca_topic_score_gemma":0.0006534694,"domain_scores_codex":[0.9984086,0.00002225079,0.0005115425,0.0003940108,0.0002874382,0.0003761655],"domain_scores_gemma":[0.9991022,0.0001498539,0.00006462199,0.0005136295,0.00004372374,0.0001259413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008097887,0.001181545,0.1467646,0.0001554315,0.000003418209,0.0004895316,0.001993706,0.0004346025,0.185673,0.002802459,0.3049367,0.3547552],"study_design_scores_gemma":[0.003720765,0.0004178263,0.03639813,0.0003424558,0.0000113405,0.00007210116,0.00008648961,0.004330697,0.008945707,0.0003435493,0.9451609,0.0001700367],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7417866,0.04615619,0.005348212,0.1304033,0.000190084,0.004315932,0.00003138515,0.0004768242,0.0712915],"genre_scores_gemma":[0.6955509,0.0116026,0.1302336,0.01364541,0.001204666,0.001058698,0.00002991504,0.000116048,0.1465582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6402242,"threshold_uncertainty_score":0.9990608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603442067637827,"score_gpt":0.3142812361172488,"score_spread":0.2982468154408705,"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."}}