{"id":"W4415744052","doi":"10.1109/iv68685.2025.00019","title":"Dynamic Conflict Surges Flagging and Visualization","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Flagging; Exploit; Dashboard; Visualization; Data visualization; Earth observation satellite","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":[0.001552184,0.001337472,0.0008381771,0.00454445,0.0006572194,0.003935349,0.001486833,0.000930321,0.007530679],"category_scores_gemma":[0.005934382,0.0005962831,0.0006733253,0.002825918,0.0003635916,0.002469863,0.003631729,0.001776515,0.002029169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003673284,"about_ca_system_score_gemma":0.001021235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003568625,"about_ca_topic_score_gemma":0.005261928,"domain_scores_codex":[0.9991923,0.0001634733,0.00007388668,0.000172505,0.0003156173,0.00008219804],"domain_scores_gemma":[0.9964501,0.001008463,0.0003638986,0.001025047,0.00084896,0.0003036215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009428039,0.0004969393,0.03134888,0.00127102,0.0003197982,0.001074667,0.004845174,0.02733424,0.04807778,0.02304212,0.1554054,0.7058412],"study_design_scores_gemma":[0.0002379455,0.0002873531,0.01998102,0.0005263649,0.0002012723,0.001044704,0.00337,0.5397193,0.07029112,0.05916068,0.3048274,0.0003528526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05210456,0.0006186439,0.8194377,0.003137992,0.0006742541,0.000528792,0.01785018,0.08983479,0.01581307],"genre_scores_gemma":[0.3163453,0.0006485844,0.6607738,0.0005088575,0.0001996816,0.0004269546,0.0131611,0.003129511,0.004806243],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007530679,"threshold_uncertainty_score":0.02519268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767175451939421,"score_gpt":0.3336972187633329,"score_spread":0.3160254642439386,"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."}}