{"id":"W4280600212","doi":"10.1002/qj.4310","title":"Extra predictability from a seamless approach for Asian summer monsoon precipitation from days to weeks","year":2022,"lang":"en","type":"article","venue":"Quarterly Journal of the Royal Meteorological Society","topic":"Climate variability and models","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Predictability; Precipitation; Climatology; Environmental science; Forcing (mathematics); Ensemble average; Range (aeronautics); Lead time; Meteorology; Scale (ratio); Monsoon; Computer science; Forecast skill; Mathematics; Statistics; Geology; Geography","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":[0.0006144356,0.0003696702,0.0002897865,0.0003425188,0.0002158856,0.0006317924,0.0003899061,0.000243841,0.0006586864],"category_scores_gemma":[0.00139671,0.0001670427,0.0005514028,0.0004115743,0.0001754726,0.0005665578,0.0008021845,0.0006086265,0.0001160547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001703374,"about_ca_system_score_gemma":0.0005787676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008580357,"about_ca_topic_score_gemma":0.008284634,"domain_scores_codex":[0.9998449,0.0000328721,0.00001314614,0.00004268393,0.00003664753,0.00002982149],"domain_scores_gemma":[0.9996324,0.0001096718,0.00005653089,0.00006588596,0.00008681626,0.00004874941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006796731,0.0001966104,0.0629729,0.0001078476,0.0002770757,0.000250111,0.0001457189,0.8105047,0.01770208,0.003767655,0.001881166,0.1015145],"study_design_scores_gemma":[0.00001467643,0.00005231631,0.01708347,0.000006140807,0.00002469257,0.00001174263,0.00003124024,0.9803112,0.001438911,0.000698837,0.0003122448,0.00001450851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379463,0.0002692346,0.05790079,0.0002054905,0.0001005367,0.00001950359,0.0008656795,0.0006070508,0.002085567],"genre_scores_gemma":[0.9935034,0.00004197271,0.005851459,0.00001250046,0.00001850522,0.000005623369,0.0004353296,0.00001916806,0.0001122024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008580357,"threshold_uncertainty_score":0.01706082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0280155917160202,"score_gpt":0.2448550263677705,"score_spread":0.2168394346517503,"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."}}