{"id":"W203537486","doi":"","title":"INFORMATION OVERLOAD IN USING CONTENT MANAGEMENT SYSTEMS: CAUSES AND CONSEQUENCES","year":2014,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Information overload; Computer science; Knowledge management; Information system; Order (exchange); Conceptual model; Relation (database); Management information systems; Empirical research; Information management; Information technology; Process management; World Wide Web; Business; Engineering","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":[0.0145068,0.000529286,0.0004647536,0.004387454,0.003328737,0.005951614,0.001242627,0.002054033,0.002220945],"category_scores_gemma":[0.08439258,0.0007467826,0.0006811499,0.002826612,0.004469498,0.005797316,0.00346763,0.001984423,0.0004659593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003248359,"about_ca_system_score_gemma":0.003058518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005317227,"about_ca_topic_score_gemma":0.003317683,"domain_scores_codex":[0.9746711,0.01193094,0.002063303,0.001298584,0.008226876,0.001809311],"domain_scores_gemma":[0.8445544,0.1079224,0.02442322,0.005770925,0.01193292,0.005395989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000661255,0.001373869,0.7150081,0.001056394,0.0002182117,0.002981644,0.09663041,0.001566879,0.005073469,0.01342835,0.004541388,0.15746],"study_design_scores_gemma":[0.0001670422,0.001079884,0.753065,0.001427081,0.0004454,0.007253621,0.1383303,0.01598499,0.008585397,0.05062688,0.022562,0.0004723676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754454,0.001437471,0.005439769,0.006319035,0.00004953245,0.0001014082,0.0000654094,0.0001493964,0.01099259],"genre_scores_gemma":[0.9971595,0.0004716925,0.001420358,0.0003778333,0.00008013286,0.00003763504,0.00002949627,0.00002213697,0.0004013477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0145068,"threshold_uncertainty_score":0.07672024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2002130469077629,"score_gpt":0.3740309913793668,"score_spread":0.1738179444716039,"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."}}