{"id":"W4220968590","doi":"10.1029/2021wr030873","title":"Extreme Sea Level Estimation Combining Systematic Observed Skew Surges and Historical Record Sea Levels","year":2022,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Tide gauge; Skew; Surge; Statistical inference; Inference; Return period; Bayesian probability; Estimation; Calibration; Bayesian inference; Computer science; Sea level; Environmental science; Econometrics; Statistics; Meteorology; Oceanography; Geography; Geology; Engineering; Mathematics; Telecommunications","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":[0.003950383,0.0001434262,0.0003456566,0.0001909285,0.001236441,0.00008228909,0.0004329971,0.00007468796,0.003997213],"category_scores_gemma":[0.0001409328,0.0001089023,0.00007523262,0.0004676086,0.0002088747,0.0001681475,0.00106774,0.0005262048,0.0002689715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007467236,"about_ca_system_score_gemma":0.00000896195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004170284,"about_ca_topic_score_gemma":0.0003943233,"domain_scores_codex":[0.995709,0.001726751,0.0003737045,0.0004756123,0.001114138,0.0006008123],"domain_scores_gemma":[0.9989979,0.0003788121,0.00006040804,0.0003776955,0.00001990146,0.0001652834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004273741,0.0008224496,0.8919997,0.00319649,0.000354941,0.0005201403,0.04329216,0.0154539,0.01627173,0.0001005182,0.02034021,0.007220396],"study_design_scores_gemma":[0.003407317,0.002159773,0.1267333,0.0006576747,0.0003841553,0.0003289909,0.004166536,0.6922593,0.00511838,0.0142461,0.1482408,0.002297585],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961722,0.0002089335,0.0002683338,0.001385809,0.00006103726,0.0003178486,0.00001125291,0.0000435457,0.001531054],"genre_scores_gemma":[0.9871441,0.000007344897,0.000376112,0.00005426639,0.00002188917,0.000149527,0.00002527685,0.00001923506,0.01220229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7652664,"threshold_uncertainty_score":0.9969133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2251830921952254,"score_gpt":0.3080802068165622,"score_spread":0.08289711462133678,"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."}}