{"id":"W4238705200","doi":"10.2139/ssrn.2459765","title":"Force and Peace: Balancing Security and Community after War","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Military and Defense Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Political science; Computer security; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003061866,0.0003768435,0.0003492529,0.002387803,0.0125118,0.009027034,0.0009939044,0.004666646,0.01501438],"category_scores_gemma":[0.006134815,0.0001847863,0.0001959953,0.00177315,0.02060746,0.008747224,0.007059108,0.00338573,0.0007002939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003148198,"about_ca_system_score_gemma":0.005022072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01034035,"about_ca_topic_score_gemma":0.02396156,"domain_scores_codex":[0.9978143,0.00101863,0.00002615405,0.0001319789,0.000184584,0.0008243005],"domain_scores_gemma":[0.9961988,0.00124721,0.0004756236,0.0001117308,0.0002928091,0.001673735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001985822,0.0002792012,0.01276629,0.00005497243,0.00002176734,0.0003314506,0.08347398,0.0002526899,0.0002525719,0.8546953,0.01044169,0.03723153],"study_design_scores_gemma":[0.0001171445,0.0001864019,0.02464963,0.0002183389,0.00002257108,0.0002570139,0.3368844,0.0005176866,0.0002027882,0.5652642,0.07164375,0.00003601195],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5719072,0.003632385,0.001546946,0.1125101,0.0006196923,0.00003632747,0.00006937633,0.00002061705,0.3096573],"genre_scores_gemma":[0.9962365,0.0002967565,0.00006919231,0.0007719583,0.0001041338,0.000008489913,0.000008840228,0.000004348365,0.00249975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01501438,"threshold_uncertainty_score":0.05022812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006492476576739976,"score_gpt":0.2582748404170969,"score_spread":0.2517823638403569,"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."}}