{"id":"W3043233900","doi":"10.1101/2020.07.10.20142679","title":"The Canadian ALS Neuroimaging Consortium (CALSNIC) - a multicentre platform for standardized imaging and clinical studies in ALS","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Toronto; University of Alberta; Université Laval; University of Calgary; McGill University; University of British Columbia","funders":"","keywords":"Neuroimaging; Amyotrophic lateral sclerosis; Medicine; Neuropsychology; Magnetic resonance imaging; Population; Disease; Medical physics; Pathology; Psychiatry; Cognition; Radiology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.07324129,0.001412928,0.001465153,0.007014436,0.005079909,0.005332795,0.004600012,0.002055395,0.01294116],"category_scores_gemma":[0.05542737,0.0006938851,0.000825833,0.009203807,0.002907257,0.001771587,0.009116777,0.001722988,0.003688396],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03200756,"about_ca_system_score_gemma":0.1785896,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7378772,"about_ca_topic_score_gemma":0.8217897,"domain_scores_codex":[0.9727179,0.009620768,0.001399779,0.002451711,0.01135286,0.002456971],"domain_scores_gemma":[0.883902,0.008784076,0.005171344,0.0116707,0.07063218,0.01983976],"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":[0.001640988,0.0003453573,0.03284825,0.0006519071,0.0003955945,0.00030297,0.001241573,0.001729371,0.002312875,0.02012758,0.7724999,0.1659037],"study_design_scores_gemma":[0.002990499,0.0003973563,0.2271426,0.001584346,0.0003730774,0.0004737567,0.001775902,0.004987108,0.002862079,0.01353348,0.7434843,0.0003955748],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"protocol","genre_scores_codex":[0.1075207,0.02665116,0.1180123,0.1300862,0.009848751,0.03226892,0.3297231,0.01274516,0.2331437],"genre_scores_gemma":[0.3321506,0.005891363,0.3346285,0.01585555,0.002678911,0.02421186,0.234662,0.003977865,0.04594333],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.9679924,"threshold_uncertainty_score":0.5273329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2002567784713174,"score_gpt":0.4490894089904219,"score_spread":0.2488326305191045,"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."}}