{"id":"W7110566276","doi":"","title":"Seeing records: remediation in Canadian archival theory & practice","year":2024,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Archival science; Environmental remediation; Best practice; Provenance; Knowledge production","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.02540514,0.0007375831,0.000768122,0.00662782,0.05222862,0.02694974,0.005415302,0.004480085,0.005859503],"category_scores_gemma":[0.03423075,0.0007179983,0.0005914774,0.009063384,0.124479,0.01330533,0.01655261,0.006989189,0.0003346804],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1753252,"about_ca_system_score_gemma":0.2302784,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9294076,"about_ca_topic_score_gemma":0.9347833,"domain_scores_codex":[0.975574,0.01183736,0.0008436433,0.002258444,0.005982498,0.003504067],"domain_scores_gemma":[0.9773815,0.01070031,0.001388373,0.003133346,0.005564881,0.001831618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001807916,0.00002847775,0.002091093,0.0001502755,0.00000771892,0.0003347505,0.4316644,0.0003684296,0.0002102055,0.538271,0.003085124,0.0237704],"study_design_scores_gemma":[0.0000182036,0.0000346223,0.003804092,0.0009358989,0.00003898965,0.000329077,0.5762694,0.001238128,0.0007666953,0.1038618,0.3125979,0.0001052036],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2622137,0.01186385,0.03280482,0.1069445,0.0007850336,0.0004143248,0.0001428739,0.000384422,0.5844464],"genre_scores_gemma":[0.9789631,0.002133617,0.005777471,0.001271642,0.00003915188,0.00005644225,0.0000284838,0.00006350174,0.01166668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9477714,"threshold_uncertainty_score":0.9565059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01496365998687561,"score_gpt":0.1930545477775293,"score_spread":0.1780908877906537,"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."}}