{"id":"W4385060835","doi":"10.53328/fclg9188","title":"Global Water Security 2023 Assessment","year":2023,"lang":"en","type":"report","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Affairs Canada; Government of Canada; McMaster University; UNICEF","keywords":"Scalability; Water security; Member states; Political science; Business; Computer science; Water resources; International trade; Ecology; Biology; European union","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":[0.003445873,0.001824672,0.0005791898,0.001999407,0.001257713,0.003342769,0.001435108,0.00319802,0.03027883],"category_scores_gemma":[0.003841348,0.0003797321,0.0009464236,0.001962674,0.000459655,0.002007999,0.002457529,0.002657209,0.01472512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006034137,"about_ca_system_score_gemma":0.03016487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1070042,"about_ca_topic_score_gemma":0.1156524,"domain_scores_codex":[0.9976593,0.0002923878,0.00005214104,0.00008893001,0.001478143,0.0004290723],"domain_scores_gemma":[0.9982643,0.0001308879,0.00008830703,0.0000735262,0.001102439,0.0003405812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009918797,0.00006239346,0.0005310934,0.0001341897,0.00001755237,0.00005278067,0.00003866203,0.0009197043,0.0002626264,0.01158259,0.9543447,0.03195447],"study_design_scores_gemma":[0.00003395603,0.00004521359,0.00297416,0.0001571383,0.00001761545,0.00002806664,0.0001181301,0.00104648,0.0006351574,0.00584563,0.989078,0.00002040999],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006162534,0.003224621,0.004481212,0.04191824,0.009447532,0.00105702,0.1695686,0.001276457,0.7628639],"genre_scores_gemma":[0.06301886,0.007961838,0.01945108,0.02788216,0.001215559,0.004307233,0.1489006,0.0009622837,0.7263004],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1070042,"threshold_uncertainty_score":0.2127628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03585974269099836,"score_gpt":0.3505379851959876,"score_spread":0.3146782425049893,"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."}}