{"id":"W6912904845","doi":"10.5683/sp3/9xhu49","title":"Data Liberation Initiative Update - National Training Day 2014","year":2014,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Training (meteorology); Data collection; Work (physics); Action (physics)","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":[0.003947819,0.002366041,0.001703576,0.005759818,0.001008851,0.003722048,0.003500126,0.002216575,0.05360676],"category_scores_gemma":[0.01982454,0.001337623,0.002047825,0.01092225,0.0006265279,0.002476185,0.003599421,0.002941529,0.09190395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003337984,"about_ca_system_score_gemma":0.005882853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09377399,"about_ca_topic_score_gemma":0.1307581,"domain_scores_codex":[0.9964731,0.0005754888,0.000510933,0.0005984891,0.001185721,0.0006562512],"domain_scores_gemma":[0.9903902,0.00169841,0.001181407,0.002060247,0.003523204,0.001146436],"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":[0.00004122319,0.00001059097,0.0007789945,0.0001765828,0.00001615924,0.000004489201,0.00001331416,0.0001069382,0.00001969412,0.0001686634,0.9973242,0.001339141],"study_design_scores_gemma":[0.0002208958,0.00001697463,0.008556428,0.0003687652,0.00003528395,0.00003043614,0.0001365959,0.0004223809,0.0002553856,0.000909012,0.9890122,0.00003551596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000972077,0.00004231457,0.00006248216,0.0001456119,0.00005531164,0.000008465892,0.9986546,0.0003767299,0.0005572377],"genre_scores_gemma":[0.0003072093,0.00003565177,0.0002105404,0.00007163093,0.00001136449,0.00006176615,0.9982486,0.0001046123,0.0009486054],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09377399,"threshold_uncertainty_score":0.1864563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161002836993979,"score_gpt":0.3402944993809767,"score_spread":0.2241942156815788,"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."}}