{"id":"W3009715926","doi":"","title":"Patterns of Long Term Storm Evolution as Represented by Pressure Proxies: Examples From Canada and Europe.","year":2008,"lang":"en","type":"article","venue":"AGUFM","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Term (time); Storm; Climatology; Meteorology; Geography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000393818,0.0002349142,0.0002092716,0.001307084,0.001266381,0.001139088,0.0007033836,0.0003504222,0.001362651],"category_scores_gemma":[0.001697515,0.0001206188,0.0002682206,0.006148474,0.0006117338,0.0003101871,0.0004630494,0.0004380139,0.0001488731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007658771,"about_ca_system_score_gemma":0.006571819,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9824554,"about_ca_topic_score_gemma":0.9891306,"domain_scores_codex":[0.9998587,0.0000173496,0.000005466599,0.00002569392,0.00004284079,0.00004994306],"domain_scores_gemma":[0.9993573,0.0001098314,0.00006630282,0.00003987249,0.0003361575,0.00009044657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000647617,0.00008240865,0.795971,0.0002550877,0.0005004111,0.0009638263,0.005119679,0.03491785,0.003994899,0.01103972,0.02764321,0.1188644],"study_design_scores_gemma":[0.00001990197,0.00001324843,0.9647295,0.00005180763,0.00006788852,0.0001350348,0.002330639,0.009892032,0.0006324971,0.001669764,0.02040753,0.00005009352],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662004,0.002773373,0.002369281,0.001210635,0.00001780632,0.00002530614,0.01095076,0.0002106659,0.01624174],"genre_scores_gemma":[0.9899002,0.001312697,0.001963011,0.00004111762,0.000003691147,0.000006864881,0.004555903,0.00004066596,0.002175905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01754463,"threshold_uncertainty_score":0.05556852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539537392191211,"score_gpt":0.205516296057882,"score_spread":0.1901209221359698,"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."}}