{"id":"W6965069639","doi":"10.3389/fneur.2020.581537.s002","title":"Data_Sheet_2_Gray Matter Matters: A Longitudinal Magnetic Resonance Voxel-Based Morphometry Study of Primary Progressive Multiple Sclerosis.docx","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; White matter; Multiple sclerosis; Percentile; Grey matter; Hippocampus; Cognition; Voxel-based morphometry; Partial volume","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000996536,0.0009600221,0.001140343,0.003291125,0.0007129574,0.001266213,0.002152685,0.0008381802,0.56345],"category_scores_gemma":[0.008423183,0.0007207401,0.0008032569,0.003719911,0.0002873514,0.001403115,0.0007635589,0.0008330168,0.08447048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005815967,"about_ca_system_score_gemma":0.001456519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007911063,"about_ca_topic_score_gemma":0.01180465,"domain_scores_codex":[0.9995783,0.00006390324,0.00009006284,0.00007068063,0.0001359285,0.00006102652],"domain_scores_gemma":[0.9951257,0.002241998,0.0006327958,0.0004681633,0.001184043,0.0003474196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007251485,0.0001574945,0.01041933,0.001948966,0.00008630755,0.0001597674,0.00006396863,0.000219619,0.0005523164,0.0004482565,0.9678128,0.017406],"study_design_scores_gemma":[0.004508635,0.0006369508,0.2149318,0.002661911,0.0002564761,0.002132489,0.0004883693,0.001362937,0.002326555,0.004703542,0.7658048,0.0001855437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001167567,0.00005071031,0.0003137098,0.0002066936,0.00005149144,0.0004332201,0.9945619,0.0004715274,0.002743305],"genre_scores_gemma":[0.01389338,0.0003611982,0.005896384,0.0009132433,0.000210798,0.006007164,0.9514269,0.0009287489,0.02036212],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.43655,"threshold_uncertainty_score":0.6226856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06527078183602436,"score_gpt":0.2473846483211481,"score_spread":0.1821138664851237,"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."}}