{"id":"W4243989385","doi":"10.1360/n072018-00314","title":"流域湿地水文调蓄功能定量评估","year":2019,"lang":"en","type":"article","venue":"SCIENTIA SINICA Terrae","topic":"Military Technology and Strategies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001274861,0.00008520531,0.000101472,0.00008359845,0.00004224955,0.00002069916,0.0002546638,0.00008793383,0.001029568],"category_scores_gemma":[0.000007929892,0.00007907629,0.0000464108,0.0001946732,0.00009056447,0.0001404471,0.00003543269,0.0001432642,0.00163818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001168341,"about_ca_system_score_gemma":0.00001163074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002854468,"about_ca_topic_score_gemma":0.00001167578,"domain_scores_codex":[0.9993851,0.000007655249,0.000124792,0.0001693869,0.00009216532,0.0002209039],"domain_scores_gemma":[0.9995539,0.00001667435,0.000008868,0.0003729977,0.00001134738,0.00003626634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005545462,0.0002614716,0.06305378,0.0005551822,0.0005046038,0.00006700191,0.002858037,0.01060823,0.2365452,0.3591619,0.2760664,0.05026273],"study_design_scores_gemma":[0.002972327,0.0006237679,0.1395919,0.0002271659,0.0001008453,0.0001115703,0.002077225,0.07518097,0.03534899,0.1291467,0.6119337,0.002684801],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.684983,0.0004527785,0.0001435648,0.0001243248,0.001231307,0.00008050827,0.000004047169,0.0006332119,0.3123473],"genre_scores_gemma":[0.9977648,0.00001649829,0.0005367483,0.00004424629,0.00002119006,0.000003614593,0.000004347547,0.000009887941,0.001598621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3358673,"threshold_uncertainty_score":0.9998837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006085898639782543,"score_gpt":0.1960404114594385,"score_spread":0.1899545128196559,"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."}}