{"id":"W7017559277","doi":"","title":"2023-10-08 - BTWRLM545 - Revenge Appropriations","year":2023,"lang":"en","type":"other","venue":"Internet Archive (Internet Archive)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sanctions; Prosperity; Government (linguistics); Nazism; World War II; Nobel laureate; Nuclear weapon; White (mutation)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011382,0.0006623669,0.0003716513,0.0009217699,0.002368338,0.006454145,0.001133328,0.003169706,0.6846412],"category_scores_gemma":[0.003558872,0.0003616316,0.0005538415,0.000878167,0.000520972,0.002589619,0.002806576,0.003141521,0.5338407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002498119,"about_ca_system_score_gemma":0.002118774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01656013,"about_ca_topic_score_gemma":0.04752011,"domain_scores_codex":[0.9989542,0.00009991979,0.00002889184,0.000120712,0.0005444955,0.0002518039],"domain_scores_gemma":[0.9988896,0.0001255677,0.00004155854,0.0001668529,0.000487523,0.0002888699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002379808,0.00002982324,0.0001158951,0.00003121282,0.00000186832,0.00004859421,0.000047129,0.00002454569,0.0002644551,0.008044075,0.9768955,0.0144732],"study_design_scores_gemma":[0.000003127886,0.000004507997,0.0001355341,0.000009355846,3.657589e-7,0.00001029249,0.00003159749,0.00001491,0.00008640139,0.0002340948,0.9994677,0.000002166088],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005055817,0.0002287354,0.0006290281,0.002971221,0.001979423,0.0001475747,0.004352404,0.001438675,0.9877472],"genre_scores_gemma":[0.001970187,0.00008457951,0.0002992151,0.001673009,0.0001227862,0.00006627684,0.001842902,0.0005664619,0.9933746],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3153588,"threshold_uncertainty_score":0.4498211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117904570281039,"score_gpt":0.261926271030005,"score_spread":0.2407472253271946,"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."}}