{"id":"W4414166423","doi":"10.1186/s44399-025-00016-8","title":"Does uptake of post-harvest handling technologies lead to better household nutrition? Empirical evidence from a project-based intervention in Northern Uganda","year":2025,"lang":"en","type":"article","venue":"BMC Agriculture","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Livelihood; Agriculture; Propensity score matching; Probit model; Descriptive statistics; Average treatment effect; Probit; Household income; Quarter (Canadian coin); Multivariate probit model","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001241562,0.0001646645,0.000183606,0.00007382048,0.00005939243,0.00003288322,0.0002790266,0.0001755728,0.00003877569],"category_scores_gemma":[0.0001608784,0.00009031822,0.00009190533,0.0004771546,0.00008563367,0.000242234,0.0001581088,0.0001757039,0.00002231633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001647302,"about_ca_system_score_gemma":0.0000118749,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213014,"about_ca_topic_score_gemma":0.03429991,"domain_scores_codex":[0.9988853,0.0000539205,0.0002841626,0.0003525486,0.0002126941,0.0002114038],"domain_scores_gemma":[0.9995676,0.00008667327,0.00007998129,0.0002288243,0.000008031672,0.00002883867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001079847,0.0004488046,0.9140103,0.00006069398,0.00001070377,0.000004770407,0.0002623161,0.009327806,0.06949919,0.000001772673,0.003185689,0.003079971],"study_design_scores_gemma":[0.0005017152,0.0001032946,0.9413419,0.0008211047,0.00001966666,4.529134e-7,0.000761827,0.00005614595,0.05375104,0.00006755421,0.00241439,0.0001608926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960544,0.0001894268,0.00107208,0.002045262,0.00007134128,0.0003754411,0.00003403846,0.00008524755,0.00007276007],"genre_scores_gemma":[0.9956185,0.0000243428,0.003571717,0.0002983451,0.00002067822,0.00009862062,0.0000341835,0.00000630798,0.0003272864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0330869,"threshold_uncertainty_score":0.9833216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827625264954266,"score_gpt":0.2605234290166583,"score_spread":0.2322471763671156,"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."}}