{"id":"W7042680299","doi":"","title":"Personal Papers and MPLP: Strategies and Techniques","year":2013,"lang":"en","type":"article","venue":"Archivaria","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information scientist; National library; Web site","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01220257,0.001308743,0.000920204,0.01101451,0.008242543,0.02591846,0.005565904,0.003521112,0.1060253],"category_scores_gemma":[0.03892592,0.001350822,0.001715685,0.01816741,0.006464865,0.02156109,0.01205807,0.003665871,0.04899875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004582874,"about_ca_system_score_gemma":0.005384946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004008482,"about_ca_topic_score_gemma":0.004202527,"domain_scores_codex":[0.9813968,0.009956771,0.001027484,0.002290546,0.004407336,0.0009209996],"domain_scores_gemma":[0.9825237,0.008211852,0.0009337343,0.005029734,0.002274684,0.001026225],"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":[0.00006165788,0.0000987172,0.0007931405,0.0005280352,0.00003021736,0.0003000383,0.007350326,0.0004415342,0.0002903467,0.6031822,0.06871257,0.3182111],"study_design_scores_gemma":[0.00001772902,0.00002819947,0.0003396994,0.0003646947,0.0000228679,0.0003745345,0.004606996,0.0007625355,0.0004579186,0.08411842,0.9088839,0.00002241028],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005105863,0.009090773,0.2142186,0.0111341,0.002056376,0.0007977581,0.0008039935,0.002369665,0.7544229],"genre_scores_gemma":[0.1129151,0.01647275,0.251306,0.002979519,0.002957096,0.002340351,0.001840184,0.00260119,0.6065879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9740815,"threshold_uncertainty_score":0.3546901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01605472882549316,"score_gpt":0.1880888949093632,"score_spread":0.1720341660838701,"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."}}