{"id":"W6889254118","doi":"10.25545/glkhd9/c9vlcv","title":"2024-06-14 14-19_model_P0.925391_S0.5_G1.0.xml","year":2024,"lang":"en","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":[0.001503377,0.003585381,0.00214099,0.003804303,0.00148034,0.004514001,0.00514636,0.003919274,0.2457564],"category_scores_gemma":[0.00851656,0.001420439,0.002105193,0.006469537,0.0007843998,0.002777209,0.002780993,0.002643113,0.355264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002372883,"about_ca_system_score_gemma":0.003033401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03912212,"about_ca_topic_score_gemma":0.05636805,"domain_scores_codex":[0.9986078,0.0002952237,0.000131711,0.000432737,0.0003138866,0.0002187231],"domain_scores_gemma":[0.9973712,0.0007409528,0.0001427709,0.0007468119,0.0007051,0.0002931397],"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":[0.00004406033,0.0000113289,0.0001383061,0.0003908749,0.0000180615,0.000008268597,0.00001565772,0.0001794295,0.00009284395,0.0004453571,0.9977094,0.0009462801],"study_design_scores_gemma":[0.0002926928,0.00001683133,0.0008067877,0.000214914,0.00002085269,0.00003315681,0.0000574503,0.0004604258,0.0004617697,0.00172255,0.9958781,0.00003434842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004710136,0.0000490797,0.00008276691,0.00008224101,0.00003332262,0.0000103567,0.9973073,0.001087275,0.001300631],"genre_scores_gemma":[0.0002060056,0.00004714141,0.0003119652,0.0000729297,0.000006834317,0.00005097109,0.9980952,0.0003470029,0.00086198],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7542436,"threshold_uncertainty_score":0.8221369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02575319490659869,"score_gpt":0.2837118134351725,"score_spread":0.2579586185285739,"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."}}