{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008912162,0.000121656,0.0003322241,0.000764581,0.0002037281,0.001387535,0.0004391327,0.00008946355,0.000002298761],"category_scores_gemma":[0.001655563,0.00007744425,0.0001298975,0.0005054326,0.00003047096,0.007611116,0.00007450032,0.0001153236,0.00002695696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004799829,"about_ca_system_score_gemma":0.00005165037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007679674,"about_ca_topic_score_gemma":0.000006763393,"domain_scores_codex":[0.9955711,0.0002388336,0.002244072,0.00005101738,0.001711267,0.0001836527],"domain_scores_gemma":[0.9934299,0.0004875177,0.004473127,0.0001792836,0.0013714,0.00005874565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003646427,0.0001062744,0.4688244,0.0008311503,0.0004809834,8.74653e-7,0.02073752,0.1385645,0.0001485601,0.3153745,0.04000713,0.01455949],"study_design_scores_gemma":[0.004689454,0.0001502452,0.2038613,0.000530981,0.0001699542,0.00006433146,0.06305016,0.09101564,0.00007545923,0.001053083,0.6349434,0.0003959579],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9593243,0.0001535959,0.02190213,0.001344103,0.00639498,0.002168072,0.0001062181,0.00003089624,0.008575704],"genre_scores_gemma":[0.9988838,0.00002023593,0.0001344623,0.0002909554,0.00006894142,0.00001960115,0.000005338291,0.000002779366,0.0005738732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5949363,"threshold_uncertainty_score":0.9996491,"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."}}