{"id":"W6960753416","doi":"10.1371/journal.pone.0138334.g002","title":"Future global development threat.","year":2015,"lang":"en","type":"other","venue":"Figshare","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Globe; Quarter (Canadian coin); International development; Cumulative effects; Sustainable development","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":[0.0006518833,0.0008701195,0.0002718113,0.002380327,0.0003999658,0.001869465,0.0006506466,0.0006674904,0.169421],"category_scores_gemma":[0.003108998,0.0003682932,0.0005850167,0.003908731,0.0002415437,0.001613253,0.001302805,0.001201463,0.05379421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225765,"about_ca_system_score_gemma":0.001900138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03307255,"about_ca_topic_score_gemma":0.04456363,"domain_scores_codex":[0.9996651,0.000033091,0.00002187714,0.00005302875,0.0001747978,0.00005201841],"domain_scores_gemma":[0.9991411,0.0001321046,0.0001095214,0.00009512381,0.0003612716,0.0001607933],"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":[0.00003970215,0.00001050461,0.002495039,0.0003396636,0.00001457559,0.00003697426,0.00008483761,0.0005296067,0.0001743914,0.005670055,0.9630523,0.02755234],"study_design_scores_gemma":[0.00002148899,0.00001291413,0.01797764,0.0001776729,0.00001321985,0.00009740391,0.0002277273,0.0004796006,0.0003127713,0.002786378,0.9778722,0.00002095687],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002288392,0.0009407944,0.003309773,0.001214579,0.0006804061,0.0001430854,0.7835159,0.005165859,0.2027412],"genre_scores_gemma":[0.04520763,0.002412583,0.01983217,0.0008948958,0.0001505173,0.000597853,0.7792981,0.003269845,0.1483364],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.169421,"threshold_uncertainty_score":0.5667697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02470747248835448,"score_gpt":0.2437406627392064,"score_spread":0.2190331902508519,"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."}}