{"id":"W1888386441","doi":"","title":"Authenticity metadata and the IPAM: progress toward the interpares application profile","year":2012,"lang":"en","type":"article","venue":"International Conference on Dublin Core and Metadata Applications","topic":"Experience-Based Knowledge Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Metadata; Presumption; Extant taxon; Computer science; Meta Data Services; Schema (genetic algorithms); World Wide Web; Information retrieval; Metadata repository; Data science; Political science","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02328503,0.0005477794,0.0007278267,0.004819957,0.001474044,0.01224889,0.004716419,0.002202363,0.004145393],"category_scores_gemma":[0.02561922,0.0007367936,0.0008005137,0.006079418,0.00488126,0.02638292,0.008049703,0.007251812,0.002926395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002958005,"about_ca_system_score_gemma":0.006712489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002487321,"about_ca_topic_score_gemma":0.001462171,"domain_scores_codex":[0.9842551,0.004445322,0.001227701,0.00117748,0.00827663,0.0006178981],"domain_scores_gemma":[0.9677354,0.008183098,0.001987827,0.01057391,0.01028492,0.001234834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001053297,0.0001880987,0.003526126,0.0006328197,0.0000168653,0.0001541065,0.001505788,0.001577289,0.004124937,0.6196471,0.01040691,0.3581147],"study_design_scores_gemma":[0.00002732443,0.0002703584,0.003826428,0.001554855,0.00003121107,0.001684263,0.003511621,0.03159288,0.01420718,0.1848084,0.7583963,0.00008922975],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02736239,0.008693513,0.7991858,0.01682821,0.0004217543,0.0004794,0.000610754,0.0053298,0.1410884],"genre_scores_gemma":[0.2552946,0.01469791,0.7008146,0.00288262,0.0008565111,0.0004797463,0.004726178,0.001334606,0.01891316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9877511,"threshold_uncertainty_score":0.1231445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09303277652311517,"score_gpt":0.3458511359965288,"score_spread":0.2528183594734136,"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."}}