{"id":"W6963882453","doi":"10.25545/glkhd9/er9tmw","title":"2024-06-16 10-44_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":[0.00133038,0.003576788,0.00219123,0.004209487,0.001499759,0.004477908,0.00531115,0.004018379,0.2338602],"category_scores_gemma":[0.008167342,0.001473556,0.002118057,0.006877297,0.0008257937,0.002836549,0.002860749,0.002496504,0.3477833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002473451,"about_ca_system_score_gemma":0.003163396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03827705,"about_ca_topic_score_gemma":0.05075551,"domain_scores_codex":[0.9986563,0.0002627618,0.0001401661,0.0004245584,0.0002939059,0.0002223006],"domain_scores_gemma":[0.9971655,0.0007711638,0.0001802577,0.0008425912,0.0007325462,0.0003079046],"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":[0.00005641776,0.00001321272,0.0001833279,0.0005207366,0.00002137563,0.00001104963,0.00001774673,0.0002052459,0.0001245179,0.0005124815,0.9973379,0.0009959339],"study_design_scores_gemma":[0.0003277987,0.00001932408,0.0010408,0.0002438443,0.00002645047,0.00004486295,0.00006749199,0.0004920392,0.0005393472,0.001731198,0.995426,0.00004089643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005664592,0.00004795004,0.00007526828,0.0000708001,0.00002682726,0.000009836668,0.9974548,0.001117972,0.001139873],"genre_scores_gemma":[0.0002274002,0.00004509278,0.0002505819,0.00005930652,0.00000564349,0.00004556579,0.9983408,0.000329343,0.0006961948],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7661398,"threshold_uncertainty_score":0.7823403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467427823892524,"score_gpt":0.2797154232652477,"score_spread":0.2550411450263225,"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."}}