{"id":"W4415081464","doi":"10.1098/rsos.250897","title":"Data-driven conflict classification exposes weak predictive indicators","year":2025,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"Global Security and Public Health","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Austrian Science Fund; Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie","keywords":"Predictability; Leverage (statistics); Discriminative model; Hierarchy; Contrast (vision); Conflict resolution research; Demographics","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":[0.01258713,0.001164628,0.001297235,0.002835066,0.0009880733,0.004746765,0.002499625,0.001557945,0.003451601],"category_scores_gemma":[0.05430895,0.0005355898,0.001153353,0.002781421,0.002336069,0.004169005,0.003791682,0.004315606,0.001340519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740685,"about_ca_system_score_gemma":0.001436608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006193286,"about_ca_topic_score_gemma":0.004104979,"domain_scores_codex":[0.9937274,0.003077593,0.0004764876,0.001256908,0.0008840236,0.0005775481],"domain_scores_gemma":[0.9369133,0.04552736,0.004829128,0.007740296,0.003822046,0.001167873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007404454,0.0004187624,0.4775665,0.0004444056,0.0004960583,0.0003346685,0.0008929628,0.3216623,0.001315328,0.04090684,0.01349394,0.1417278],"study_design_scores_gemma":[0.00002056502,0.00006384101,0.02679591,0.0001491289,0.00003726851,0.00007623787,0.000302428,0.8833534,0.0008480283,0.0860395,0.002269426,0.00004431133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5081071,0.0008441865,0.4664969,0.006353768,0.0002967543,0.0002566045,0.006128596,0.001338931,0.01017723],"genre_scores_gemma":[0.9721465,0.000113938,0.02323487,0.0002967774,0.0000911166,0.0001076856,0.003160136,0.00007129569,0.0007778906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01258713,"threshold_uncertainty_score":0.0665679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06839054696917884,"score_gpt":0.3979567157357529,"score_spread":0.329566168766574,"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."}}