{"id":"W6964073080","doi":"10.25545/glkhd9/fmrblk","title":"2024-06-06 09-23_model_P0.925391_S0.5_G1.0.xml","year":2024,"lang":"ko","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[0.001276101,0.003233517,0.002062675,0.004083789,0.001414629,0.004641689,0.004584756,0.00378248,0.24643],"category_scores_gemma":[0.008149523,0.001435536,0.001971314,0.006351879,0.00078764,0.002751377,0.002837451,0.002390837,0.363919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002330388,"about_ca_system_score_gemma":0.002870756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03565179,"about_ca_topic_score_gemma":0.0458842,"domain_scores_codex":[0.9987702,0.0002331528,0.0001292334,0.0003930356,0.0002708868,0.000203503],"domain_scores_gemma":[0.9972372,0.000757279,0.0001692205,0.0008241404,0.0007186573,0.0002935182],"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":[0.00005344159,0.00001133563,0.000177746,0.0004642812,0.00001905879,0.00001034115,0.00001750822,0.0001768613,0.0001118312,0.0005008525,0.9974517,0.001005013],"study_design_scores_gemma":[0.0002764335,0.00001676151,0.001021625,0.0002298594,0.00002360904,0.00004176747,0.00006181668,0.0003986809,0.0004857341,0.001667834,0.9957371,0.00003864639],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000533404,0.00004657364,0.00007620452,0.00007442142,0.00002661249,0.00000917645,0.9972736,0.001134107,0.001305901],"genre_scores_gemma":[0.000264153,0.00004989995,0.0002494986,0.00006376971,0.000006143687,0.0000452863,0.9980891,0.000392081,0.0008400501],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.75357,"threshold_uncertainty_score":0.8243904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02504834940518516,"score_gpt":0.2798813581443677,"score_spread":0.2548330087391826,"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."}}