{"id":"W2913837121","doi":"10.5038/1911-9933.13.2.1700","title":"#StopThisMovie and the Pitfalls of Mass Atrocity Prevention: Framing of Violence and Anticipation of Escalation in Burundi’s Crisis (2015-2017)","year":2019,"lang":"en","type":"article","venue":"Genocide Studies and Prevention","topic":"Global Peace and Security Dynamics","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Framing (construction); Genocide; Political science; Anticipation (artificial intelligence); Criminology; Psychology; Geography; Law; 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":[0.003186634,0.0003844425,0.0001716571,0.0008186576,0.01094451,0.005500717,0.0006137684,0.002056788,0.009750025],"category_scores_gemma":[0.004731069,0.0001914258,0.0001877876,0.0007982366,0.009266748,0.004354926,0.004575782,0.003831007,0.0007538799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004890207,"about_ca_system_score_gemma":0.003110102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01245171,"about_ca_topic_score_gemma":0.02907128,"domain_scores_codex":[0.9979563,0.001487079,0.0000417592,0.0001098177,0.0001567574,0.000248308],"domain_scores_gemma":[0.9982253,0.0008207187,0.0003515626,0.0001260025,0.0002591249,0.000217292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001296375,0.00006204138,0.01465306,0.0002617286,0.0000113573,0.0006083797,0.4431202,0.0001291422,0.0006693374,0.4183862,0.04435298,0.07761601],"study_design_scores_gemma":[0.00001439745,0.00014124,0.01774001,0.001094075,0.0000184633,0.0004048164,0.3677143,0.0003851129,0.001037397,0.04612496,0.5652832,0.00004209296],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4476659,0.009357081,0.006409045,0.2374536,0.002485089,0.00008106251,0.0002162272,0.0001084034,0.2962235],"genre_scores_gemma":[0.9723155,0.00146529,0.001411073,0.004056191,0.0001262746,0.00005457442,0.00005847982,0.00004863902,0.02046398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01245171,"threshold_uncertainty_score":0.0354811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179488331430761,"score_gpt":0.3441012905907799,"score_spread":0.3223064072764723,"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."}}