{"id":"W7002192062","doi":"","title":"Military Spending and Economic Growth: A 2025 Update","year":2025,"lang":"en","type":"article","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Capitalism; Human rights; Government (linguistics); Public spending","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003625981,0.002083297,0.001759055,0.009343545,0.0007489981,0.004900797,0.001873112,0.004284248,0.02621757],"category_scores_gemma":[0.007498985,0.0007350263,0.001575104,0.01215999,0.0008148956,0.00879029,0.003849894,0.004028787,0.01285124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003591995,"about_ca_system_score_gemma":0.006219391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01705245,"about_ca_topic_score_gemma":0.02635395,"domain_scores_codex":[0.998966,0.0001347106,0.0002491426,0.00008293035,0.0003842011,0.0001830541],"domain_scores_gemma":[0.9948207,0.001250257,0.0008456845,0.0001072419,0.001908065,0.001068092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001491707,0.000115172,0.003541565,0.003264758,0.00009369785,0.00009852693,0.00008735915,0.0004487171,0.00006687099,0.004450562,0.6703638,0.3173198],"study_design_scores_gemma":[0.00002763822,0.0000774228,0.01127773,0.01242207,0.00012308,0.0001864586,0.0003826058,0.0003009165,0.00009219771,0.002910041,0.9721411,0.0000586203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.002233919,0.8222944,0.001022452,0.07461074,0.03643512,0.0001275326,0.02684228,0.0004870529,0.03594649],"genre_scores_gemma":[0.027506,0.8558508,0.002573899,0.03966023,0.02054822,0.0004420069,0.03570469,0.0001841158,0.01753004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02621757,"threshold_uncertainty_score":0.08770657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097132446779869,"score_gpt":0.2775758547484611,"score_spread":0.2666045302806624,"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."}}