{"id":"W6950489295","doi":"10.5281/zenodo.6957770","title":"Onshape Research Guide","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Data collection; Government (linguistics); Work (physics); Context (archaeology); Key (lock)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002362303,0.001314824,0.001185257,0.004667366,0.001230072,0.004467856,0.003064853,0.001942225,0.6768346],"category_scores_gemma":[0.00601634,0.001140024,0.0006794844,0.005090036,0.0005347135,0.003815201,0.002899993,0.001811891,0.651678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001282122,"about_ca_system_score_gemma":0.004944245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006764569,"about_ca_topic_score_gemma":0.01953926,"domain_scores_codex":[0.9986492,0.0001256722,0.00006496238,0.0001435999,0.0009194753,0.00009699669],"domain_scores_gemma":[0.9952205,0.0009667109,0.0001401395,0.0008553809,0.00228122,0.0005360678],"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":[0.00003167911,0.00001948725,0.00004181216,0.0001846994,0.000002537207,0.00002281865,0.00003118674,0.0001026023,0.0005347298,0.002128866,0.9530541,0.04384532],"study_design_scores_gemma":[0.000007123655,0.000004321799,0.00006156928,0.00003610063,0.000001642408,0.00002369972,0.00001432676,0.0000551013,0.0002445053,0.0008285399,0.9987174,0.000005739897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005039959,0.001604328,0.02412897,0.001594409,0.0007280906,0.0006751035,0.09383222,0.0418025,0.8351305],"genre_scores_gemma":[0.001688047,0.002027092,0.0190626,0.0009638556,0.0001688335,0.0007368764,0.07508441,0.01619102,0.8840773],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6768346,"threshold_uncertainty_score":0.4609562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07358744176974373,"score_gpt":0.3097603344746298,"score_spread":0.236172892704886,"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."}}