{"id":"W2548630225","doi":"10.1108/rmj-02-2016-0006","title":"Assisting the appraisal of e-mail records with automatic classification","year":2016,"lang":"en","type":"article","venue":"Records Management Journal","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Communication source; Data science; Value (mathematics); Originality; Knowledge management; World Wide Web; Qualitative research; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.01642812,0.000783827,0.000822277,0.003238785,0.001025449,0.004684545,0.001780234,0.001365179,0.00337806],"category_scores_gemma":[0.1096223,0.0003805248,0.0005506612,0.001919807,0.0008199278,0.004590788,0.001496787,0.001674141,0.003669107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352518,"about_ca_system_score_gemma":0.001992359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002419486,"about_ca_topic_score_gemma":0.002898984,"domain_scores_codex":[0.9795131,0.0136863,0.001183162,0.001826723,0.003103997,0.000686666],"domain_scores_gemma":[0.8524232,0.1055538,0.01190859,0.01094655,0.01818911,0.0009787783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001242058,0.001201207,0.07016435,0.001474575,0.00009610896,0.0002336097,0.01311612,0.003326425,0.02566868,0.002631807,0.009631601,0.8712135],"study_design_scores_gemma":[0.000423092,0.003499627,0.2436836,0.00331882,0.0006643567,0.001694417,0.03880809,0.4670783,0.1216618,0.03154293,0.08677655,0.0008482937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7432338,0.0009115321,0.2227149,0.004311803,0.0003437035,0.001982685,0.001011026,0.006744508,0.01874602],"genre_scores_gemma":[0.7685405,0.0003199596,0.2250474,0.0005820207,0.0001497342,0.0005814917,0.001024292,0.0001690161,0.003585639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01642812,"threshold_uncertainty_score":0.08688128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2058599394170367,"score_gpt":0.4188411557116751,"score_spread":0.2129812162946383,"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."}}