{"id":"W2519002810","doi":"","title":"The Impact of Key Words on Knowledge Reuse in Emergency Management Social Media","year":2016,"lang":"en","type":"article","venue":"Americas Conference on Information Systems","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Reuse; Knowledge management; Social media; Key (lock); Computer science; Seekers; Knowledge sharing; Contingency; Set (abstract data type); Cognition; Personal knowledge management; Emergency management; World Wide Web; Computer security; Engineering; Psychology; Organizational learning; Political science","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":[0.003397244,0.0004213788,0.0003875457,0.004854898,0.001626041,0.005685171,0.0006793905,0.0009854255,0.005093334],"category_scores_gemma":[0.09354459,0.0002631776,0.0006317246,0.005303019,0.002275654,0.008509983,0.003256284,0.001146732,0.0009278167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634088,"about_ca_system_score_gemma":0.001453319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007266317,"about_ca_topic_score_gemma":0.0068598,"domain_scores_codex":[0.9924887,0.003006539,0.0008201614,0.0006777798,0.002222503,0.0007842988],"domain_scores_gemma":[0.8138744,0.1590494,0.01203034,0.004583504,0.008623931,0.0018383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002817097,0.001151661,0.6168206,0.001516844,0.0006132435,0.002681969,0.06212489,0.003254861,0.01425186,0.00871498,0.002997244,0.2830547],"study_design_scores_gemma":[0.000125966,0.0009970305,0.8390498,0.0005796661,0.001091269,0.002792387,0.09906491,0.01106613,0.01039177,0.01839403,0.01621227,0.0002348574],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853801,0.0006462726,0.001452193,0.000402154,0.00003023574,0.00005552846,0.0002050561,0.00005284977,0.01177564],"genre_scores_gemma":[0.9977652,0.0002216541,0.0006455385,0.00004295125,0.00002109153,0.00001899343,0.0001249387,0.0000293984,0.001130271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007266317,"threshold_uncertainty_score":0.01796657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0588211147442279,"score_gpt":0.3540011756888398,"score_spread":0.2951800609446119,"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."}}