{"id":"W2161049692","doi":"10.5334/sta.cu","title":"Inter-ethnic Cooperation Revisited: Why mobile phones can help prevent discrete events of violence, using the Kenyan case study","year":2013,"lang":"en","type":"article","venue":"Stability International Journal of Security and Development","topic":"Political Conflict and Governance","field":"Social Sciences","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile phone; Kenya; Population; Public relations; Set (abstract data type); Computer security; Internet privacy; Phone; Political science; Business; Sociology; Engineering; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003834873,0.0004752813,0.0002650644,0.001212485,0.01870091,0.002899596,0.0008108145,0.002780318,0.00346938],"category_scores_gemma":[0.005834311,0.0002846124,0.0003449503,0.001243335,0.006145759,0.003501244,0.003680762,0.001869943,0.0003263486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003096343,"about_ca_system_score_gemma":0.00306278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01824986,"about_ca_topic_score_gemma":0.0449971,"domain_scores_codex":[0.9958407,0.003262572,0.000080245,0.0001528323,0.0002009686,0.0004626467],"domain_scores_gemma":[0.9974086,0.001810858,0.0003177087,0.0001110055,0.0001534841,0.0001983421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001577807,0.0004565053,0.05533367,0.0005213717,0.00004923509,0.01669855,0.7156611,0.001167372,0.001620679,0.1404842,0.006551767,0.0612978],"study_design_scores_gemma":[0.0000411404,0.0002190551,0.02222027,0.0006865662,0.00004489276,0.002889583,0.8959518,0.001187522,0.001137206,0.008326226,0.06725438,0.0000413074],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8986643,0.001384794,0.003001885,0.01353039,0.00008784411,0.0002286117,0.00004750418,0.000008407944,0.08304618],"genre_scores_gemma":[0.9956595,0.0006136443,0.000943501,0.0003734624,0.000009673163,0.00008122677,0.000009502093,0.000002233878,0.002307204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01870091,"threshold_uncertainty_score":0.03628731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04059732857554711,"score_gpt":0.3514331936567004,"score_spread":0.3108358650811533,"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."}}