{"id":"W2088133484","doi":"10.1002/2013eo030006","title":"The Need for Improved Maps of Global Cropland","year":2013,"lang":"en","type":"article","venue":"Eos","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Food security; Agricultural economics; Agriculture; Consumption (sociology); Natural resource economics; Production (economics); Competition (biology); Business; Agricultural productivity; Key (lock); Population; Economics; Geography; Ecology; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00164301,0.001232981,0.0005471991,0.008377125,0.0005753189,0.002315478,0.001392525,0.0009718437,0.02496034],"category_scores_gemma":[0.008161427,0.0006226389,0.0007247304,0.01610822,0.0004725154,0.006062514,0.002374115,0.001961041,0.007160053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324325,"about_ca_system_score_gemma":0.00193207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03585768,"about_ca_topic_score_gemma":0.0455954,"domain_scores_codex":[0.9993895,0.0001735913,0.00006587317,0.0001041478,0.0002170735,0.00004981286],"domain_scores_gemma":[0.9955162,0.0006738626,0.0004788956,0.001008138,0.002120174,0.0002028267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001079218,0.0001533699,0.02059085,0.002265156,0.0002306017,0.0002612182,0.0008824448,0.03939094,0.003321975,0.0393316,0.2827008,0.6107631],"study_design_scores_gemma":[0.00002633793,0.00002978558,0.02816692,0.0005918878,0.00005285956,0.0002573445,0.001083872,0.0111221,0.000792486,0.0266527,0.9311357,0.00008796783],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"commentary","genre_scores_codex":[0.04713553,0.02968246,0.2975826,0.02677319,0.003443243,0.0007055174,0.3667392,0.01661,0.2113284],"genre_scores_gemma":[0.18148,0.02898151,0.5637457,0.001496122,0.0005886593,0.001109068,0.2065412,0.002491151,0.01356642],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.03585768,"threshold_uncertainty_score":0.08350062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00895440020585426,"score_gpt":0.196202834404175,"score_spread":0.1872484341983207,"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."}}