{"id":"W7098591618","doi":"","title":"WENDGLOUMDE AGNES ZABSONRE WELFARE COMPARISONS WHEN POPULATIONS DIFFER IN SIZE","year":2014,"lang":"en","type":"article","venue":"","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Welfare; Test (biology); Welfare system; Human welfare","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":[0.008698082,0.0002579766,0.0004963689,0.001855285,0.001549914,0.001295132,0.0006169084,0.0007311929,0.01309489],"category_scores_gemma":[0.02938833,0.0002310114,0.00066308,0.001535441,0.0006654036,0.001740617,0.00205116,0.001217705,0.001667931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00175387,"about_ca_system_score_gemma":0.002454837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03064653,"about_ca_topic_score_gemma":0.07296527,"domain_scores_codex":[0.9946056,0.003312723,0.0002981107,0.0003821963,0.0009795885,0.0004218706],"domain_scores_gemma":[0.9923103,0.003745177,0.0007678248,0.0004860224,0.002136878,0.0005538664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003567947,0.000610844,0.3388105,0.0007475197,0.0006767051,0.000747262,0.01524642,0.0009287923,0.002578706,0.04550913,0.2579695,0.3326066],"study_design_scores_gemma":[0.0001451323,0.0006446711,0.7452136,0.001071787,0.0002451263,0.0004438556,0.01636484,0.0007080749,0.001785373,0.01845346,0.2148102,0.0001139849],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7207429,0.02036922,0.007018787,0.1531574,0.00661405,0.0004501954,0.006444193,0.00008852648,0.0851147],"genre_scores_gemma":[0.8688404,0.009131394,0.004695321,0.01303594,0.001152227,0.0009624988,0.002938204,0.0001436475,0.09910041],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03064653,"threshold_uncertainty_score":0.06093627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07002056619723813,"score_gpt":0.4010065992776504,"score_spread":0.3309860330804122,"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."}}