{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001104481,0.0009541084,0.0007919166,0.001628064,0.0009650081,0.001015478,0.001557698,0.001299714,0.1532115],"category_scores_gemma":[0.006497657,0.0006142872,0.0007037589,0.003219904,0.0001495959,0.001177099,0.001259168,0.001359,0.03671106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00176145,"about_ca_system_score_gemma":0.003102172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08902907,"about_ca_topic_score_gemma":0.08867326,"domain_scores_codex":[0.9992431,0.0001296852,0.0001582292,0.0001690632,0.000152518,0.0001474423],"domain_scores_gemma":[0.9972785,0.000360655,0.0003491296,0.0002746702,0.001533661,0.0002034122],"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":[0.0001177349,0.00005110517,0.007645294,0.0006669018,0.0000388765,0.00004321888,0.00009483562,0.0001442084,0.00008868531,0.0005003975,0.9865599,0.00404892],"study_design_scores_gemma":[0.002196522,0.0001929509,0.255332,0.002500742,0.000163764,0.000208281,0.002508595,0.001219923,0.000506361,0.002156975,0.7328998,0.0001141187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007837734,0.00001586497,0.0000845975,0.00008541458,0.00002770034,0.000291219,0.9973339,0.0000358426,0.00134165],"genre_scores_gemma":[0.005847427,0.0000877557,0.001008675,0.0003080769,0.00003153838,0.007647173,0.9796003,0.0000469271,0.005422177],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1532115,"threshold_uncertainty_score":0.5125434,"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."}}