{"id":"W4221054007","doi":"10.1002/joc.7608","title":"A 247‐year tree‐ring reconstruction of spring temperature and relation to spring flooding in eastern boreal Canada","year":2022,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of Winnipeg; Université du Québec en Abitibi-Témiscamingue; Université du Québec à Montréal","funders":"","keywords":"Boreal; Snowmelt; Spring (device); Flooding (psychology); Climatology; Environmental science; Dendrochronology; Snow; Taiga; Climate change; Paleoclimatology; Physical geography; Geology; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003185784,0.00007208621,0.0001871008,0.0003807592,0.00005255092,0.00002204902,0.0001926098,0.00003072762,0.00008737153],"category_scores_gemma":[0.0001376566,0.00007232467,0.00003127728,0.0001205701,0.00002237878,0.0001759446,0.0000447674,0.0002578549,0.000001048511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006064733,"about_ca_system_score_gemma":0.0001660017,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08774476,"about_ca_topic_score_gemma":0.3530228,"domain_scores_codex":[0.9988587,0.0001085071,0.000446866,0.0001127263,0.0003354165,0.0001377838],"domain_scores_gemma":[0.9993203,0.0002094782,0.0002821992,0.00004932323,0.00007834714,0.00006035738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003398852,0.00000661528,0.9811291,0.0000082972,0.00002733511,0.0001668812,0.00016193,0.008440068,0.0005482968,0.0001692047,0.000004230034,0.00899823],"study_design_scores_gemma":[0.0004931695,0.00008050865,0.9938909,0.00006937116,0.000006635321,0.001612055,0.0006280178,0.002608494,0.0002160405,0.00006285361,0.0002659381,0.0000659714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974036,0.0001638197,0.00001539477,0.0007921865,0.001023565,0.00004196533,0.00002207107,0.000003879458,0.0005334888],"genre_scores_gemma":[0.9988507,0.00004133496,0.0009893298,0.00004264058,0.00006294845,4.175014e-7,0.000002788347,0.000003327659,0.000006505175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.265278,"threshold_uncertainty_score":0.91833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097489683738838,"score_gpt":0.2307258602362982,"score_spread":0.2197509633989098,"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."}}