{"id":"W6964288874","doi":"10.25545/glkhd9/5uwucx","title":"2024-06-13 00-23_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":[0.001316171,0.00361285,0.002195498,0.004250342,0.001471762,0.00455073,0.005217853,0.004010173,0.244353],"category_scores_gemma":[0.008016528,0.001475014,0.002051363,0.006774007,0.0008210513,0.002795594,0.00286893,0.002419568,0.3552336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002461634,"about_ca_system_score_gemma":0.003084132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03763806,"about_ca_topic_score_gemma":0.04809425,"domain_scores_codex":[0.998696,0.0002488877,0.0001351867,0.0004164236,0.000286747,0.0002166837],"domain_scores_gemma":[0.997187,0.0007817382,0.0001824171,0.0008290762,0.0007169526,0.0003027816],"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":[0.0000584495,0.00001294634,0.0001839514,0.0005421201,0.00002136841,0.0000113472,0.00001820247,0.0001939141,0.0001268507,0.0005264653,0.9972938,0.001010666],"study_design_scores_gemma":[0.0003152656,0.00001792842,0.00104123,0.0002409138,0.00002596921,0.000044124,0.00006612072,0.0004342615,0.0005328064,0.001688867,0.9955522,0.00004023905],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005269431,0.00004573187,0.0000754989,0.00006739666,0.0000247991,0.000009182854,0.997471,0.001077694,0.001176066],"genre_scores_gemma":[0.0002314387,0.00004675474,0.0002496997,0.00006007247,0.00000563633,0.00004557947,0.9982645,0.0003573736,0.0007389992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7556471,"threshold_uncertainty_score":0.8174421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02358063214786479,"score_gpt":0.2768421371349574,"score_spread":0.2532615049870925,"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."}}