{"id":"W4285726342","doi":"10.1002/mrm.29387","title":"Community‐Organized Resources for Reproducible<scp>MRS</scp>Data Analysis","year":2022,"lang":"en","type":"letter","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"National Institute on Aging","keywords":"Computer science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01599767,0.0007899563,0.001091336,0.002815827,0.00503296,0.004361394,0.003775408,0.01525346,0.2736196],"category_scores_gemma":[0.06870804,0.0009241157,0.001377344,0.001937647,0.001727887,0.003743439,0.007861328,0.008144045,0.2170596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002019723,"about_ca_system_score_gemma":0.01001794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004433816,"about_ca_topic_score_gemma":0.01566412,"domain_scores_codex":[0.9909066,0.002705012,0.0006272805,0.000541185,0.004009891,0.001210076],"domain_scores_gemma":[0.913324,0.0279298,0.002823806,0.01288733,0.03205056,0.01098449],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002913984,0.00001657035,0.00007309244,0.00003593606,0.00000290838,0.0002059542,0.0000222914,0.00001417994,0.000328295,0.0009906064,0.9868974,0.01138376],"study_design_scores_gemma":[0.00009252191,0.00002351739,0.0004939259,0.0001358182,0.000006657913,0.0004409034,0.0001346892,0.0002341234,0.0005892576,0.008976631,0.9888446,0.00002739257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.001594757,0.001712624,0.03527382,0.6655551,0.02882954,0.0020176,0.009253721,0.01450115,0.2412617],"genre_scores_gemma":[0.0227394,0.002123485,0.04713603,0.4149745,0.03730051,0.003951467,0.0119366,0.01007246,0.4497656],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9840024,"threshold_uncertainty_score":0.9153486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06269216935421451,"score_gpt":0.3514557479783547,"score_spread":0.2887635786241402,"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."}}