{"id":"W4406774768","doi":"10.3389/frai.2024.1472236","title":"Enhancing Africa’s agriculture and food systems through responsible and gender inclusive AI innovation: insights from AI4AFS network","year":2025,"lang":"en","type":"article","venue":"Frontiers in Artificial Intelligence","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Food security; Sustainability; Agriculture; Sustainable agriculture; Food systems; Transformative learning; Software deployment; Business; Participatory action research; Environmental resource management; Economic growth; Economics; Engineering; Sociology; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01187947,0.000408703,0.0002214529,0.0008568285,0.008084032,0.007150081,0.0008661171,0.001611846,0.002477719],"category_scores_gemma":[0.009046493,0.0001672792,0.0002370731,0.000952635,0.01004955,0.005972155,0.007822093,0.002503841,0.0002775659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00702722,"about_ca_system_score_gemma":0.008245953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004654779,"about_ca_topic_score_gemma":0.008924242,"domain_scores_codex":[0.9902852,0.007584507,0.0001107861,0.0003694719,0.0005788764,0.001071211],"domain_scores_gemma":[0.9913092,0.006329641,0.0006610866,0.0003167714,0.0004182995,0.0009650601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001035578,0.0002090285,0.01612438,0.0004353269,0.00002284387,0.002049575,0.6757684,0.0009898813,0.002598361,0.2037066,0.007902804,0.09008926],"study_design_scores_gemma":[0.0000214427,0.0001673365,0.008059559,0.0006424381,0.0000217458,0.000611605,0.5544339,0.001522135,0.001417793,0.07003047,0.3630275,0.00004395999],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7232095,0.002255357,0.01386064,0.05736188,0.0002363951,0.0002012157,0.0001098359,0.00005378609,0.2027114],"genre_scores_gemma":[0.9901934,0.001273674,0.003206524,0.001502961,0.00001972534,0.0001101308,0.00002982115,0.00002000542,0.003643763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01187947,"threshold_uncertainty_score":0.06282532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040530000059408,"score_gpt":0.2558128659374719,"score_spread":0.2254075659368778,"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."}}