{"id":"W2589575306","doi":"10.29173/cais125","title":"Improving Personal and Social Information Management with Advanced Tagging","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Personal account; Computer science; Personal information management; Personally identifiable information; Internet privacy; Business; World Wide Web; Management information systems; Information system; Engineering; Computer security; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.007539616,0.0008859358,0.0007203405,0.003090691,0.001689074,0.006516653,0.001859367,0.001778741,0.002938316],"category_scores_gemma":[0.01592328,0.0007100767,0.00115215,0.003219476,0.001166057,0.01084155,0.004784883,0.001956186,0.003496976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051567,"about_ca_system_score_gemma":0.001924345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003454426,"about_ca_topic_score_gemma":0.00511118,"domain_scores_codex":[0.9952069,0.001889325,0.0003989427,0.0009061733,0.001389343,0.0002092005],"domain_scores_gemma":[0.9885505,0.004540391,0.0007945218,0.004069698,0.001645363,0.0003996438],"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":[0.0003216091,0.0008626263,0.01753085,0.0007016323,0.000204762,0.0003885811,0.01094421,0.01207843,0.03597183,0.05352114,0.01411807,0.8533562],"study_design_scores_gemma":[0.00009158991,0.0005008987,0.01804379,0.0005451005,0.0004998816,0.001190388,0.005735138,0.4047665,0.06990212,0.1570035,0.3411717,0.0005493896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03873481,0.0004336813,0.9399253,0.001349267,0.0001677504,0.0003405766,0.0002333674,0.006530207,0.012285],"genre_scores_gemma":[0.2325119,0.0006557257,0.7492285,0.0004764404,0.0001438951,0.0003070621,0.0008906259,0.0008037384,0.01498207],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007539616,"threshold_uncertainty_score":0.03987378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101275199276334,"score_gpt":0.2283766152034748,"score_spread":0.2173638632107115,"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."}}