{"id":"W4323047633","doi":"10.5194/egusphere-2022-852-ac2","title":"Reply on RC2","year":2023,"lang":"en","type":"peer-review","venue":"","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Ministry of Science and Technology, Taiwan; Academia Sinica; Global Lake Ecological Observatory Network","keywords":"Typhoon; Environmental science; Dissolved organic carbon; Stratification (seeds); Subtropics; Ecosystem; Hydrology (agriculture); Monsoon; Lake ecosystem; Oceanography; Inflow; Ecology; Geology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006116707,0.0002658833,0.0003817251,0.00002826603,0.00008082389,0.00002120586,0.0004873709,0.0001882907,0.04219684],"category_scores_gemma":[0.0008073729,0.0001867802,0.0001541138,0.0003398667,0.0001337628,0.00002274599,0.0004340762,0.0004850074,0.09562721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001809378,"about_ca_system_score_gemma":0.000009679709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009175254,"about_ca_topic_score_gemma":0.00009825028,"domain_scores_codex":[0.9979043,0.00006836239,0.0002919484,0.0006935203,0.0006683982,0.0003734661],"domain_scores_gemma":[0.9989436,0.0001534115,0.0001167202,0.0006607926,0.000005761294,0.0001196606],"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":[0.000001232676,0.00001840288,0.00001512139,0.00009333548,0.000004922244,0.00002959246,0.000002727724,0.0003289046,0.000002545564,0.000009980698,0.9903174,0.009175822],"study_design_scores_gemma":[0.00003272041,0.00009987308,0.00009427529,0.000791016,0.00002279282,0.000005358248,1.49884e-7,0.0001912267,0.000006229847,0.0003207481,0.9982027,0.0002328814],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00029913,0.0003384845,0.00001160562,0.1754985,0.00251367,0.0004030549,0.00004979113,0.000801297,0.8200845],"genre_scores_gemma":[0.00008674987,0.0005410298,0.0003440065,0.07191081,0.0001759067,0.00002738336,0.000144095,0.00005053129,0.9267195],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.106635,"threshold_uncertainty_score":0.9586787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06951189450486074,"score_gpt":0.3139567726992264,"score_spread":0.2444448781943657,"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."}}