{"id":"W4401741328","doi":"10.1016/j.catena.2024.108325","title":"River profile and relict landscape analysis reveal the Cenozoic geomorphic evolution of the Nihewan Basin in North China","year":2024,"lang":"en","type":"article","venue":"CATENA","topic":"Geological formations and processes","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nuclear Safety Commission; University of Toronto","funders":"Institute of Mountain Hazards and Environment; National Key Research and Development Program of China; China Scholarship Council; University of Toronto; National Natural Science Foundation of China","keywords":"Cenozoic; China; Structural basin; Geology; Drainage basin; Paleontology; Southern china; Geography; Physical geography; Earth science; Archaeology; Cartography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000178273,0.0001392798,0.0001697785,0.001904703,0.0005663197,0.0004324035,0.0002481934,0.0001730961,0.001335046],"category_scores_gemma":[0.0002627704,0.000191399,0.0001746994,0.002263732,0.0003694806,0.0003386902,0.0004259599,0.0001123775,0.000116506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007369007,"about_ca_system_score_gemma":0.0009317775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07023127,"about_ca_topic_score_gemma":0.1907813,"domain_scores_codex":[0.9999082,0.000009893993,0.000007742472,0.000031915,0.00001684607,0.00002537705],"domain_scores_gemma":[0.9998983,0.00001074449,0.00002621995,0.0000127123,0.00002782775,0.00002420162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004589052,0.00001868088,0.9724638,0.00002844452,0.00005140842,0.0002037841,0.001623602,0.0007786173,0.006385414,0.0006671131,0.0002373079,0.01749595],"study_design_scores_gemma":[0.000001158781,0.000004836199,0.9985251,0.000002051182,0.000008315547,0.00002858599,0.0003167346,0.0006444422,0.0000567239,0.00005182532,0.0003576602,0.000002517726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990363,0.0000392965,0.00007531424,0.00001661226,6.9513e-7,0.000001952575,0.00009529006,0.000005212979,0.0007292092],"genre_scores_gemma":[0.9994462,0.00002579383,0.0000645369,0.000003522343,7.41372e-7,0.000001822321,0.000125126,0.000002015262,0.0003302542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07023127,"threshold_uncertainty_score":0.1396449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007041636688648214,"score_gpt":0.1804766765899437,"score_spread":0.1734350399012954,"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."}}