{"id":"W4288060570","doi":"10.18357/kula.234","title":"Knowledge Lost, Knowledge Gained","year":2022,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Ontario Council of University Libraries; University of Toronto","funders":"","keywords":"Computer science; World Wide Web; Metadata; Archivist; Context (archaeology); Data science; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0125639,0.0005979748,0.0009485874,0.005223869,0.01014352,0.03276819,0.003581303,0.003416146,0.01790124],"category_scores_gemma":[0.04884306,0.0004879678,0.0006843086,0.004699318,0.03309567,0.04026547,0.01788524,0.005749649,0.003277315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01255775,"about_ca_system_score_gemma":0.01768818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01346337,"about_ca_topic_score_gemma":0.01003399,"domain_scores_codex":[0.9878251,0.004026292,0.0009224623,0.001703816,0.004187635,0.001334668],"domain_scores_gemma":[0.9725747,0.009555231,0.00193186,0.007214145,0.005560138,0.003163888],"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":[0.000219833,0.0001597133,0.007321126,0.0008960374,0.0001004257,0.002165155,0.2321735,0.0007343138,0.0009937735,0.4164242,0.03907617,0.2997358],"study_design_scores_gemma":[0.00003830251,0.0001140752,0.003182892,0.001087348,0.00007036488,0.001322762,0.1641406,0.0005548881,0.000844607,0.2548852,0.5736732,0.0000858779],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2305666,0.02421848,0.03162659,0.1434798,0.004008519,0.000261905,0.001183301,0.0006625723,0.5639922],"genre_scores_gemma":[0.913289,0.006456614,0.006046822,0.005152396,0.0005907998,0.0001145617,0.0003974136,0.0002338824,0.06771843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03276819,"threshold_uncertainty_score":0.09111327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08202230126807764,"score_gpt":0.3304454973673931,"score_spread":0.2484231960993155,"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."}}