{"id":"W3124015744","doi":"","title":"Seasonal Poverty in Madagascar: Magnitude and Solutions","year":2003,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Seasonality; Poverty; Malnutrition; Wet season; Psychological intervention; Agriculture; Productivity; Toll; Geography; Socioeconomics; Dry season; Consumption (sociology); Agricultural economics; Economic shortage; Food insecurity; Environmental health; Economics; Food security; Biology; Ecology; Economic growth; Medicine","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":[0.0006330922,0.0003875997,0.0002561495,0.001339265,0.0009198591,0.001773498,0.0006252129,0.0007645156,0.003446752],"category_scores_gemma":[0.001556336,0.0001689476,0.0002592744,0.001843124,0.0008108658,0.00129565,0.00185854,0.0006010589,0.0001005438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002373897,"about_ca_system_score_gemma":0.001915682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03055982,"about_ca_topic_score_gemma":0.05389562,"domain_scores_codex":[0.999687,0.000111994,0.00001418547,0.00002814019,0.00004129658,0.0001173488],"domain_scores_gemma":[0.9993647,0.0001386505,0.0002062072,0.0000180287,0.0001261822,0.0001462565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004339493,0.0003058011,0.5460261,0.001774904,0.0003807496,0.002820895,0.00676648,0.0105512,0.001616185,0.06454447,0.02802331,0.3367559],"study_design_scores_gemma":[0.00004788154,0.0004582757,0.7993973,0.001249041,0.0002595311,0.002553811,0.0690179,0.02109649,0.0005198208,0.04802759,0.05728262,0.00008968556],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8278798,0.04429304,0.003480114,0.08685671,0.0004313502,0.0001862942,0.002424114,0.0001230218,0.03432565],"genre_scores_gemma":[0.9908324,0.007023333,0.0005665108,0.0004481802,0.0001424467,0.00003338739,0.000174424,0.000003584997,0.0007757224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03055982,"threshold_uncertainty_score":0.06076384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703069035852865,"score_gpt":0.2245256302997261,"score_spread":0.2074949399411975,"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."}}