{"id":"W6925822350","doi":"10.21223/p3/m3zmkr","title":"Dataset for: MAMA SASHA Cross-sectional Endline Household Survey","year":2017,"lang":"en","type":"dataset","venue":"International Potato Center","topic":"Education and Technology Integration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Livelihood; Food security; General partnership; Government (linguistics); Agriculture; Intervention (counseling); Kenya; Sustainability; Public health; Consumption (sociology)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001243495,0.0002719258,0.0002398552,0.0003219297,0.0007488155,0.0007448301,0.001893596,0.0006150544,0.002274013],"category_scores_gemma":[0.002136494,0.0002804078,0.0001646125,0.0000650834,0.0005075947,0.0004132456,0.0001573085,0.0005014897,0.0006239207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003712809,"about_ca_system_score_gemma":0.0004385445,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007239655,"about_ca_topic_score_gemma":0.04833373,"domain_scores_codex":[0.997692,0.0001448294,0.0005028663,0.0005835419,0.0007067142,0.0003700213],"domain_scores_gemma":[0.997726,0.0003133789,0.0005608563,0.0006739659,0.0005979483,0.0001278474],"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":[0.00005769174,0.0002634764,0.05681724,0.000007329385,0.0001149218,0.000004181184,0.00003009731,0.000001067024,7.474151e-7,0.0005618319,0.9420188,0.0001226256],"study_design_scores_gemma":[0.0005253548,0.00002488501,0.04523823,0.00002665068,0.00001302687,0.000007347991,0.00003241256,0.000004306779,0.00000482009,0.0003500969,0.9535236,0.0002493105],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00121582,0.00002519237,0.00007197243,0.002086889,0.00981925,0.0003935783,0.9856559,0.00005601915,0.0006753581],"genre_scores_gemma":[0.004325527,0.0001907509,0.0001065993,0.001050768,0.001891499,0.0001306962,0.9874023,0.0000234916,0.004878336],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04109407,"threshold_uncertainty_score":0.9999648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1122741443551418,"score_gpt":0.4465585730884655,"score_spread":0.3342844287333237,"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."}}