{"id":"W4396799260","doi":"10.1038/s41597-024-03306-z","title":"How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?","year":2024,"lang":"en","type":"article","venue":"Scientific Data","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"National Aeronautics and Space Administration","keywords":"Land cover; Agriculture; Land use; Agricultural land; Environmental resource management; Satellite; Work (physics); Monitoring and evaluation; Remote sensing; Geography; Environmental science; Ecology; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007667767,0.0001090961,0.0001176105,0.00004114551,0.0001855442,0.00125534,0.0008072424,0.00004893981,0.0001416222],"category_scores_gemma":[0.00004593837,0.00007027168,0.00002760695,0.0005246617,0.00002766332,0.001116644,0.0005254738,0.00007624349,0.0008696436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004580062,"about_ca_system_score_gemma":0.00001024429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007550903,"about_ca_topic_score_gemma":0.004481896,"domain_scores_codex":[0.998577,0.00002234725,0.0001393261,0.0007137127,0.0002384794,0.00030912],"domain_scores_gemma":[0.9992094,0.00004352764,0.00004831337,0.0006259787,0.000006738119,0.00006603419],"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":[0.000008365366,0.00003829387,0.005799801,0.0002662684,0.00001160438,0.00003529554,0.0002716316,0.0002627996,0.004387576,0.00001353052,0.9866046,0.002300187],"study_design_scores_gemma":[0.0001470761,0.000006607312,0.002978714,0.0001826201,0.0000132317,0.000004296735,0.0000767626,0.01638979,0.0004345393,0.0002580119,0.9793559,0.0001524682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9354371,0.00873334,0.0005722436,0.004553655,0.00742319,0.001723679,0.0310899,0.0003361416,0.01013078],"genre_scores_gemma":[0.9904572,0.00004098366,0.0001777112,0.00003429161,0.0001590559,0.0000302695,0.003091999,0.00001347029,0.005995062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05502009,"threshold_uncertainty_score":0.9999083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05920618791904884,"score_gpt":0.2583645116580236,"score_spread":0.1991583237389748,"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."}}