{"id":"W3009365419","doi":"","title":"Poverty measurements in an imprecise environment","year":2003,"lang":"en","type":"article","venue":"Revue d'ECONOMIE et de MANAGEMENT","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Poverty; Mathematics; Computer science; Economics; Economic growth","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":[0.004754313,0.0005906181,0.001039552,0.002303503,0.0008650961,0.003973955,0.0009190899,0.001125634,0.001191641],"category_scores_gemma":[0.03525756,0.0005113654,0.0004906441,0.003922583,0.003630784,0.007650408,0.003704505,0.001964037,0.0002112415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149526,"about_ca_system_score_gemma":0.0005960279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003953982,"about_ca_topic_score_gemma":0.003088113,"domain_scores_codex":[0.9909918,0.005132612,0.0004167381,0.0009001861,0.002120809,0.0004378705],"domain_scores_gemma":[0.9795798,0.01350907,0.002676967,0.002428524,0.001485724,0.0003198907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009785922,0.0001573092,0.05455769,0.0003695372,0.0004074608,0.0003897225,0.001792332,0.3455019,0.003260448,0.4778805,0.00292101,0.1117835],"study_design_scores_gemma":[0.00002633631,0.000215467,0.04229349,0.0002273067,0.00009300243,0.0003508269,0.001826767,0.2232914,0.004940782,0.7194057,0.007132492,0.0001964915],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4929803,0.002599702,0.4864737,0.001922711,0.0001853593,0.00003314264,0.002372964,0.0001855843,0.01324648],"genre_scores_gemma":[0.9696838,0.0006998684,0.02860047,0.00008820686,0.00006877575,0.00004400066,0.0002454309,0.000033531,0.000536004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004754313,"threshold_uncertainty_score":0.02514356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06904330934669102,"score_gpt":0.3137012759640166,"score_spread":0.2446579666173256,"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."}}