{"id":"W4248396262","doi":"10.1515/iupac.88.1498","title":"White Matter","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.0008368528,0.001788311,0.001820827,0.005006033,0.0008998433,0.003416193,0.002474887,0.001951956,0.1625926],"category_scores_gemma":[0.01174906,0.0005369674,0.001511782,0.007820812,0.0004489153,0.002811639,0.001985648,0.001847269,0.163486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001108526,"about_ca_system_score_gemma":0.002543371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209968,"about_ca_topic_score_gemma":0.02538108,"domain_scores_codex":[0.9988633,0.0001341729,0.0002532933,0.0004338313,0.0001904177,0.0001250395],"domain_scores_gemma":[0.9965832,0.0008648052,0.000582366,0.0008222743,0.000917623,0.0002297313],"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":[0.0001313513,0.00001384624,0.001761129,0.002261112,0.00008344446,0.00007517888,0.00002714103,0.0001107287,0.000143496,0.0007385526,0.9787183,0.01593561],"study_design_scores_gemma":[0.0001510746,0.00002321076,0.00933619,0.002042301,0.0001048699,0.0005284678,0.00008082623,0.0002130147,0.0002998537,0.004644231,0.982527,0.00004911807],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002928212,0.0009076791,0.0002411785,0.0002077844,0.0001111907,0.00003841202,0.9929894,0.0004355665,0.00477596],"genre_scores_gemma":[0.001229005,0.0008642944,0.0008069023,0.0003430357,0.00007242613,0.0002060568,0.993238,0.0001576425,0.003082668],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1625926,"threshold_uncertainty_score":0.5439264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487649783676308,"score_gpt":0.4989379978597195,"score_spread":0.4501730194920888,"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."}}