{"id":"W6997618131","doi":"","title":"Worldwide Droughts Report (2023-2025)","year":2025,"lang":"en","type":"other","venue":"Internet Archive (Internet Archive)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resilience (materials science); Population; Natural disaster; Climate change; Famine; Extreme weather; Sustainability; Quarter (Canadian coin)","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":[0.0009920865,0.001059148,0.000340187,0.001195039,0.0008817069,0.002185281,0.0008676966,0.001276021,0.1042486],"category_scores_gemma":[0.001707984,0.0002468986,0.0004697326,0.002349062,0.000164299,0.001435163,0.001696254,0.001628316,0.05513515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001448329,"about_ca_system_score_gemma":0.004740099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05692798,"about_ca_topic_score_gemma":0.06395338,"domain_scores_codex":[0.9995177,0.00003948147,0.00003294355,0.00003072933,0.0002516641,0.0001276025],"domain_scores_gemma":[0.9992636,0.00003866313,0.00008299407,0.00002900967,0.0004068894,0.000178826],"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":[0.00003399983,0.00001068236,0.0002300064,0.0001256462,0.000003678188,0.00003014629,0.0000174613,0.0000501057,0.00006271269,0.0006899689,0.988672,0.01007354],"study_design_scores_gemma":[0.00002093746,0.00001041749,0.005190114,0.0001675969,0.000008073489,0.00002442491,0.0001060624,0.00007081627,0.0001713944,0.0004431449,0.993775,0.00001197793],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002384642,0.004998488,0.00137644,0.01137478,0.009838681,0.0004772063,0.5304607,0.002240684,0.4368484],"genre_scores_gemma":[0.03939456,0.009224773,0.004414568,0.01360421,0.001970636,0.001629506,0.4648192,0.001628569,0.463314],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1042486,"threshold_uncertainty_score":0.3487462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131589656121411,"score_gpt":0.2649819107439966,"score_spread":0.2518229451318555,"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."}}