{"id":"W2167577015","doi":"10.1002/mrm.20215","title":"Multiple mouse biological loading and monitoring system for MRI","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"University of Toronto","keywords":"Computer science; Nuclear magnetic resonance; Physics","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":[0.001095895,0.000896399,0.0007999464,0.0007380371,0.0003806678,0.0004442286,0.001342783,0.0008991319,0.006757882],"category_scores_gemma":[0.0006148355,0.0004708486,0.0005405878,0.0002857462,0.000347147,0.000721273,0.0007910833,0.001609091,0.003122152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003212135,"about_ca_system_score_gemma":0.0004133244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002156213,"about_ca_topic_score_gemma":0.0004616996,"domain_scores_codex":[0.9993615,0.00007953148,0.00005127319,0.0002172362,0.0002314819,0.00005914214],"domain_scores_gemma":[0.9992707,0.000104798,0.0001373904,0.0002282544,0.0001408159,0.0001180966],"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":[0.0002722654,0.0001281735,0.0002895167,0.00009140131,0.00001441952,0.00006757215,0.00005094338,0.000155228,0.9822376,0.0004594838,0.001724518,0.01450885],"study_design_scores_gemma":[0.00008936221,0.00138735,0.002740188,0.00003527567,0.00008587293,0.0007255977,0.00001732949,0.004764578,0.9574905,0.0001952584,0.03241297,0.00005568159],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.146035,0.001098837,0.8280731,0.0005066097,0.0005529027,0.00221002,0.001333043,0.01558311,0.004607441],"genre_scores_gemma":[0.2832814,0.001874689,0.6792831,0.001032656,0.0002721102,0.008399128,0.003079094,0.001223224,0.0215546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006757882,"threshold_uncertainty_score":0.02260739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03970556124456874,"score_gpt":0.329105762926873,"score_spread":0.2894002016823042,"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."}}