{"id":"W2373141237","doi":"","title":"A Unsteady Flow Model for River Network in Littoral Area of South China","year":2000,"lang":"en","type":"article","venue":"","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Hydrology (agriculture); Outflow; Littoral zone; Environmental science; Unsteady flow; China; Network model; Drainage network; Water resource management; Geography; Geology; Meteorology; Drainage basin; Oceanography; Computer science; Geotechnical engineering; Cartography; Archaeology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001049309,0.00009197959,0.0001085655,0.000005496409,0.00005743923,0.00000734608,0.000176177,0.00003437976,0.004096897],"category_scores_gemma":[0.000001700843,0.00005396373,0.00005211246,0.0001545863,0.0001744816,0.0001858921,0.00005224237,0.00003901093,0.0000928789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000044254,"about_ca_system_score_gemma":0.000001733096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003130493,"about_ca_topic_score_gemma":0.0003209146,"domain_scores_codex":[0.9992012,0.00001072973,0.0001492334,0.0002151156,0.000171586,0.000252128],"domain_scores_gemma":[0.9998215,0.00001042147,0.00002808394,0.00007866089,6.061728e-7,0.00006076425],"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":[0.00001948219,0.00006795669,0.06962369,0.000001935727,0.000001582481,4.957386e-7,0.001032427,0.9033515,0.0006647052,0.00002407553,0.001429641,0.02378248],"study_design_scores_gemma":[0.0002734325,0.0000641633,0.3479346,0.000009823316,0.000003992046,8.351531e-7,0.00006946822,0.6488407,0.000207868,0.001835781,0.0006077023,0.0001516406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843696,0.00001385727,0.0006037109,0.0001297073,0.0000188354,0.0001982702,0.00001002053,0.00001180342,0.0146442],"genre_scores_gemma":[0.9809182,0.00001098831,0.008091031,0.0001024427,0.00001903827,0.00001328766,0.000004895804,0.000002620225,0.01083747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2783109,"threshold_uncertainty_score":0.9968135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009501426127447227,"score_gpt":0.1795926880066092,"score_spread":0.170091261879162,"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."}}