{"id":"W4319988945","doi":"10.1016/j.heliyon.2023.e13001","title":"Corrigendum to “Measuring the poverty reduction effects of adopting agricultural technologies in rural Ethiopia: Findings from an endogenous switching regression approach”","year":2023,"lang":"en","type":"erratum","venue":"Heliyon","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Poverty reduction; Agriculture; Poverty; Economics; Reduction (mathematics); Endogeny; Regression; Econometrics; Agricultural economics; Economic growth; Mathematics; Geography; Statistics; Biology; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002244345,0.0007570902,0.0007590121,0.001707179,0.001338153,0.00169054,0.001271945,0.001281196,0.05022436],"category_scores_gemma":[0.03887869,0.0003142387,0.0008886238,0.002197786,0.0006912302,0.0008781019,0.0009573363,0.002838729,0.01136766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931428,"about_ca_system_score_gemma":0.002079949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03224587,"about_ca_topic_score_gemma":0.03623402,"domain_scores_codex":[0.9983924,0.0004849003,0.0001571034,0.0002042813,0.0006675779,0.0000937459],"domain_scores_gemma":[0.9798073,0.009072608,0.0007131709,0.0007789939,0.00922983,0.0003980932],"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":[0.00001647408,0.000016727,0.0006598533,0.0001244052,0.00001338639,0.0001166082,0.0001107868,0.0001598907,0.00004737214,0.000846095,0.9858338,0.01205457],"study_design_scores_gemma":[0.00005017776,0.0001032989,0.0175321,0.0006351517,0.0001483793,0.0004340505,0.001415726,0.00194801,0.001023374,0.004182214,0.972434,0.00009336442],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.009082705,0.005404914,0.007455137,0.1912254,0.7432421,0.0001871483,0.009408721,0.0008410818,0.03315267],"genre_scores_gemma":[0.1603566,0.02470177,0.01735572,0.1234307,0.10168,0.0008627956,0.01296509,0.002055022,0.5565923],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05022436,"threshold_uncertainty_score":0.1680172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05230382290798914,"score_gpt":0.2544798181756987,"score_spread":0.2021759952677096,"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."}}