{"id":"W2591838676","doi":"","title":"Data-driven knowledge mobilization","year":2016,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Toronto","funders":"","keywords":"Knowledge management; Workforce; Context (archaeology); Business; Scale (ratio); Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004063827,0.0001047561,0.00008840209,0.0002107893,0.0001458021,0.0003216382,0.0007503137,0.00002610692,0.00002173893],"category_scores_gemma":[0.0003747372,0.00007212786,0.000009219655,0.0006688299,0.0001234955,0.003539863,0.001028392,0.00003625678,0.00009947574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001886168,"about_ca_system_score_gemma":0.00003254972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007699471,"about_ca_topic_score_gemma":0.000004639718,"domain_scores_codex":[0.9990785,0.000001329664,0.0001174362,0.0003890543,0.0001914572,0.0002222328],"domain_scores_gemma":[0.9992493,0.00005713838,0.0000347083,0.0004261983,0.0002143485,0.00001833487],"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":[0.000003213591,0.00004612384,0.01942267,0.00020337,0.000008081714,0.000005667232,0.00005174449,0.001337408,0.002689974,0.008955391,0.005961968,0.9613144],"study_design_scores_gemma":[0.0001767339,0.000006899663,0.02216734,0.0002422702,0.00001212293,0.000008304117,0.00000430711,0.7653073,0.0002514156,0.0001762895,0.2112801,0.0003669119],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03538903,0.00009998609,0.9631844,0.0001159165,0.0008577024,0.00006618971,0.000005410032,0.0002285945,0.00005274333],"genre_scores_gemma":[0.9729663,0.00003691355,0.02514801,0.0002656081,0.001491387,0.00000621682,0.00002044452,0.00001839273,0.0000467701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9609475,"threshold_uncertainty_score":0.3101565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05958826494740582,"score_gpt":0.2687864063518581,"score_spread":0.2091981414044523,"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."}}