{"id":"W4205242326","doi":"10.1017/cjn.2021.73","title":"CJN volume 48 issue 3 Cover and Front matter","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Front cover; Front (military); Volume (thermodynamics); Cover (algebra); Content (measure theory); Environmental science; Forestry; Computer science; Mathematics; Geography; Meteorology; Engineering; Physics; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001090236,0.0008776501,0.0008698815,0.002530028,0.001821143,0.005802499,0.001018174,0.002339991,0.839525],"category_scores_gemma":[0.004780542,0.0003063602,0.0005688908,0.001416457,0.0007525549,0.001331487,0.001488546,0.002206225,0.7143227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002653523,"about_ca_system_score_gemma":0.004013066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008272471,"about_ca_topic_score_gemma":0.01914552,"domain_scores_codex":[0.9989303,0.00006295308,0.00005328948,0.000138677,0.0006830316,0.0001316665],"domain_scores_gemma":[0.995532,0.0003866391,0.0001149313,0.0002836071,0.002041661,0.001641084],"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":[0.0000193434,0.00002490452,0.0001457599,0.00007648829,0.000002697474,0.00005926542,0.000006916554,0.00001924786,0.0001649477,0.0004829145,0.9673235,0.03167399],"study_design_scores_gemma":[0.000007631771,0.000007993407,0.0008104668,0.0001256553,0.000002381426,0.0001533853,0.00002495017,0.00005113495,0.0001181724,0.0002929101,0.9984003,0.000004979519],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0009642288,0.004222362,0.0003675809,0.01145796,0.04883591,0.0001140724,0.002703579,0.0009683942,0.9303659],"genre_scores_gemma":[0.002542814,0.002183859,0.0002780885,0.002598137,0.006089942,0.00003139027,0.001082358,0.000334791,0.9848585],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.160475,"threshold_uncertainty_score":0.228898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617708106145297,"score_gpt":0.2156837977562256,"score_spread":0.1795067166947726,"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."}}