{"id":"W2993168059","doi":"10.5194/cp-16-1043-2020","title":"Application and evaluation of the dendroclimatic process-based model MAIDEN during the last century in Canada and Europe","year":2020,"lang":"en","type":"article","venue":"Climate of the past","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"Fonds De La Recherche Scientifique - FNRS; Agence Nationale de la Recherche","keywords":"Calibration; Dendrochronology; Environmental science; Climate change; Context (archaeology); Tree (set theory); Taiga; Climatology; Bayesian probability; Precipitation; Computer science; Meteorology; Statistics; Geography; Mathematics; Geology; Forestry","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":[0.001645636,0.0006043288,0.0003837175,0.0005968109,0.0008795392,0.001146026,0.001112673,0.000598099,0.0008797492],"category_scores_gemma":[0.002422336,0.0002720566,0.0005436168,0.0007483959,0.0003529853,0.0005274093,0.0005734969,0.0005496238,0.00009862109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008964545,"about_ca_system_score_gemma":0.00567182,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8650522,"about_ca_topic_score_gemma":0.8092418,"domain_scores_codex":[0.9997475,0.00005385774,0.00001373203,0.00008507245,0.00005091578,0.00004902134],"domain_scores_gemma":[0.9991581,0.0002944195,0.00006583524,0.0000572878,0.0003456851,0.00007861365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001905713,0.00006418402,0.08746021,0.00004961725,0.0001005876,0.0001035558,0.0001299218,0.8996794,0.000884174,0.00123785,0.0003608296,0.009739094],"study_design_scores_gemma":[0.00003214642,0.00004017996,0.03887345,0.00001776617,0.00002905752,0.00002434076,0.000105149,0.9585395,0.0009529916,0.0002484235,0.001114253,0.00002269741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936148,0.0001851304,0.003406571,0.0001012229,0.00001055901,0.00002391352,0.0008410856,0.0001574388,0.001659186],"genre_scores_gemma":[0.9964809,0.00007712663,0.00224531,0.00001083389,0.00000250622,0.00001232946,0.0006823296,0.00002005274,0.0004685685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1349478,"threshold_uncertainty_score":0.2714851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689923977634866,"score_gpt":0.2240970557397282,"score_spread":0.2071978159633796,"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."}}