{"id":"W4311548688","doi":"10.1163/9789004322714_cclc_2020-0151-0766","title":"Climatic Changes, Water Systems, and Adaptation Challenges in Shawi Communities in the Peruvian Amazon","year":2022,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Amazon rainforest; Climate change; Geography; Deforestation (computer science); Livelihood; Photovoice; Environmental science; Indigenous; Agriculture; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009193594,0.0002909161,0.0004122578,0.0005320652,0.0007161062,0.0002897436,0.0001885344,0.0002225154,0.0002808185],"category_scores_gemma":[0.000007156066,0.0002186566,0.00003184421,0.000235453,0.0000913957,0.0002323752,0.000150396,0.0005693813,0.000003411706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000167654,"about_ca_system_score_gemma":0.000003235497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01480469,"about_ca_topic_score_gemma":0.1567406,"domain_scores_codex":[0.9978405,0.0008531347,0.0003731891,0.0003075535,0.0002359118,0.0003897269],"domain_scores_gemma":[0.9993246,0.0001703338,0.0001306076,0.0003073241,0.00002841481,0.00003867659],"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":[0.001507457,0.001375348,0.0010344,0.02267906,0.00007262323,0.0001388066,0.2197144,0.00001668535,0.00001394737,0.0007121703,0.7484332,0.0043019],"study_design_scores_gemma":[0.001268544,0.0004809739,0.0008929775,0.0007266862,0.00007203718,0.0001103193,0.03061598,0.0006078427,0.000004853956,0.0001115979,0.9647601,0.0003480579],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05925921,0.05471449,2.804194e-7,0.01979117,0.003761353,0.006514899,0.854916,0.0001480629,0.000894471],"genre_scores_gemma":[0.0528713,0.1086539,0.000002554981,0.001393474,0.0004528059,0.001995143,0.834574,0.00004193376,0.00001478996],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.216327,"threshold_uncertainty_score":0.9917558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1570778316530734,"score_gpt":0.2950197922999946,"score_spread":0.1379419606469212,"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."}}