{"id":"W4393462810","doi":"10.5281/zenodo.4276552","title":"NPRI data for open IO Canada","year":2020,"lang":"en","type":"dataset","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001228081,0.0007672611,0.001106822,0.0002045367,0.0004559137,0.002092558,0.02446239,0.0005347893,0.00001695452],"category_scores_gemma":[0.0005912859,0.0007904064,0.0001618942,0.0008055791,0.00004637629,0.0007151488,0.009987972,0.0008594381,0.00006447614],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007559349,"about_ca_system_score_gemma":0.005904112,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8256947,"about_ca_topic_score_gemma":0.7584531,"domain_scores_codex":[0.9949474,0.0002553203,0.0009710747,0.001876523,0.0007686911,0.00118096],"domain_scores_gemma":[0.9910734,0.0004107871,0.0007737433,0.006852725,0.0002038215,0.0006854722],"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":[0.00002593812,0.00007944601,0.00002639916,0.0001974703,0.0001170443,0.0001466853,0.00001242814,0.0005145011,0.000004262706,0.00219676,0.994925,0.001754074],"study_design_scores_gemma":[0.0004306493,0.0001040014,0.00006476055,0.0001360306,0.00004307125,0.00008249533,0.000006436487,0.1235011,0.00001866322,0.0003467592,0.874488,0.0007780581],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[7.27266e-7,0.0004352304,0.4366325,0.004118681,0.0006956616,0.001370455,0.5564268,0.0002579348,0.00006199803],"genre_scores_gemma":[0.0002016678,0.00009291782,0.06452232,0.006945898,0.0006108716,0.0005627124,0.926536,0.00005984359,0.0004677248],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3721102,"threshold_uncertainty_score":0.9997315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03137076904340503,"score_gpt":0.2662491858258907,"score_spread":0.2348784167824857,"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."}}