{"id":"W7015862585","doi":"","title":"Un Ã©vÃªque Ã  Vatican II, Mgr. Albert Sanschagrin, o.m.i","year":2000,"lang":"de","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Relation (database); Subject (documents); Context (archaeology); Period (music)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00123821,0.0007126697,0.0007485236,0.001739635,0.002877433,0.004234319,0.000751108,0.00138186,0.1998218],"category_scores_gemma":[0.002724322,0.000338966,0.0002922116,0.001604677,0.0009036874,0.001800732,0.001541513,0.002148851,0.2062857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002209567,"about_ca_system_score_gemma":0.003080976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01503268,"about_ca_topic_score_gemma":0.03126489,"domain_scores_codex":[0.9993486,0.00006432556,0.00002349907,0.0001350552,0.0003484764,0.00008011563],"domain_scores_gemma":[0.9985359,0.000187455,0.00006659151,0.00005709182,0.0007231369,0.0004299289],"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":[0.00003555496,0.00001119875,0.0001862362,0.00007341847,0.000001865322,0.00004541663,0.00007576404,0.00003860411,0.0001505566,0.003673019,0.9285055,0.06720293],"study_design_scores_gemma":[0.000001805734,0.000005544617,0.0002202993,0.00006314046,0.000001563518,0.00006995907,0.00006491659,0.00003612708,0.0001416107,0.0005073259,0.998884,0.000003722604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00251765,0.1549673,0.005725898,0.1971256,0.04660571,0.0001110833,0.002749533,0.002459187,0.587738],"genre_scores_gemma":[0.003253656,0.02171301,0.001173419,0.003923507,0.001266087,0.0000226815,0.0004035356,0.0003350621,0.967909],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1998218,"threshold_uncertainty_score":0.6684704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001258196881905367,"score_gpt":0.1365894341847244,"score_spread":0.135331237302819,"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."}}