{"id":"W2912660807","doi":"10.1007/s13253-019-00356-4","title":"New Exploratory Tools for Extremal Dependence: $$\\chi $$ Networks and Annual Extremal Networks","year":2019,"lang":"en","type":"preprint","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria","funders":"National Science Foundation of Sri Lanka; National Science Foundation","keywords":"Estimator; Spatial dependence; Statistics; Scale (ratio); Mathematics; Econometrics; Block (permutation group theory); Variance (accounting); Precipitation; Extreme value theory; Geography; Meteorology; Combinatorics; Economics; Cartography","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":[0.004314125,0.0006291713,0.0007142915,0.004291742,0.0009069536,0.001923044,0.00135559,0.0009694946,0.003532298],"category_scores_gemma":[0.03898809,0.0005124303,0.000974216,0.002947967,0.002320932,0.003793382,0.002474799,0.002177224,0.000347979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101883,"about_ca_system_score_gemma":0.0007035838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002836785,"about_ca_topic_score_gemma":0.00302665,"domain_scores_codex":[0.9983596,0.000936956,0.00007837468,0.0003281427,0.0002146257,0.0000822068],"domain_scores_gemma":[0.9659432,0.02604336,0.003185038,0.002599976,0.001414569,0.0008138199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001778223,0.000109833,0.05800722,0.0003004541,0.0003566094,0.0004898182,0.001706931,0.1445304,0.0020722,0.6828529,0.007625972,0.1017699],"study_design_scores_gemma":[0.00002128552,0.00003964553,0.01173404,0.00008998837,0.00004432271,0.0002769681,0.000349108,0.4343568,0.0006702362,0.5436772,0.008691475,0.00004895911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0568391,0.0004261991,0.9373119,0.0006599175,0.00003682919,0.00006517383,0.0007610907,0.0004704992,0.003429409],"genre_scores_gemma":[0.6362196,0.0005883827,0.3582614,0.0002859826,0.000203885,0.0004672679,0.001694379,0.000335285,0.001943812],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004314125,"threshold_uncertainty_score":0.02281553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03130763794268528,"score_gpt":0.2260244532449348,"score_spread":0.1947168153022495,"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."}}