{"id":"W2129790001","doi":"10.1002/nbm.965","title":"Automatic repositioning of single voxels in longitudinal <sup>1</sup>H MRS studies","year":2005,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Voxel; Reproducibility; Computer science; Orientation (vector space); Artificial intelligence; Pattern recognition (psychology); Nuclear medicine; Mathematics; Medicine; Statistics","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":[0.001642411,0.0006106738,0.0007483745,0.0008013963,0.0004171074,0.0006520915,0.001149037,0.0006898945,0.002527996],"category_scores_gemma":[0.006468005,0.0005778011,0.0002846693,0.0006596857,0.0007434723,0.0007884165,0.000730768,0.0007897135,0.001014551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000203555,"about_ca_system_score_gemma":0.0005972859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005840509,"about_ca_topic_score_gemma":0.001438803,"domain_scores_codex":[0.999289,0.0002403551,0.00007582465,0.0001487786,0.0001865412,0.00005936998],"domain_scores_gemma":[0.9962598,0.001638219,0.0006291465,0.001019095,0.0003678104,0.00008598719],"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":[0.001550343,0.00008483598,0.00260012,0.0004030747,0.00005183793,0.0004421806,0.0002985777,0.004993168,0.7343288,0.0008678038,0.001313264,0.2530661],"study_design_scores_gemma":[0.00009175421,0.0008602023,0.02237809,0.00004952814,0.000114125,0.004429205,0.0001687229,0.02237694,0.9375595,0.001407257,0.01042027,0.0001443516],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2193843,0.002597041,0.7703614,0.0002562257,0.0002282973,0.0003388445,0.0003256452,0.004987449,0.001520873],"genre_scores_gemma":[0.3606923,0.0008304925,0.6348644,0.000146652,0.00006112281,0.0002525849,0.0003637061,0.0009924695,0.001796381],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002527996,"threshold_uncertainty_score":0.008686006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04993633119147617,"score_gpt":0.3771785005555256,"score_spread":0.3272421693640494,"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."}}