{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002180023,0.0002296133,0.0001583616,0.001034823,0.000834772,0.0006067993,0.000423927,0.0001573225,0.0007898193],"category_scores_gemma":[0.0004196299,0.0001280883,0.000263165,0.001403173,0.0001944483,0.0001473164,0.0002615384,0.0001907446,0.0001421933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004774729,"about_ca_system_score_gemma":0.004690218,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9695733,"about_ca_topic_score_gemma":0.9862332,"domain_scores_codex":[0.9998976,0.000005574571,0.000005209557,0.00003066611,0.00002315832,0.00003777719],"domain_scores_gemma":[0.9995595,0.00002445588,0.00005374874,0.00002280621,0.0002456058,0.00009397676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007401099,0.00002319415,0.9858337,0.00001586568,0.00006065261,0.0001025947,0.0002559219,0.002379191,0.001743122,0.00008586424,0.0007873637,0.008638506],"study_design_scores_gemma":[0.000001816205,0.000004934434,0.9969626,0.000004582053,0.000009559641,0.00002422064,0.0002241763,0.001982866,0.0001181547,0.000008416488,0.000653145,0.00000551367],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960031,0.0001277368,0.0001828383,0.00002147466,0.000002584837,0.000006529863,0.002947642,0.00002169026,0.0006864383],"genre_scores_gemma":[0.9966463,0.00007681613,0.0003438492,0.000005557419,0.000001274682,0.000003674509,0.002584536,0.000004567853,0.0003332152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03042674,"threshold_uncertainty_score":0.06121182,"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."}}