{"id":"W2799373456","doi":"10.1016/j.quageo.2018.04.008","title":"High-resolution age modelling of peat bogs from northern Alberta, Canada, using pre- and post-bomb 14C, 210Pb and historical cryptotephra","year":2018,"lang":"en","type":"article","venue":"Quaternary Geochronology","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Ministry of Advanced Education, Government of Alberta; Canada Research Chairs; Canada Foundation for Innovation; University of Alberta","keywords":"Peat; Bog; Ombrotrophic; Tephra; Geology; Permafrost; Macrofossil; Physical geography; Radiocarbon dating; Holocene; Hydrology (agriculture); Earth science; Archaeology; Paleontology; Oceanography; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000141572,0.0001757433,0.0003589765,0.0001005154,0.0002378144,0.00001088876,0.0001835977,0.0002545534,0.0007669478],"category_scores_gemma":[0.00003506344,0.0001603641,0.00002494395,0.00006722839,0.0005827892,0.0001154204,0.00005337608,0.000235658,0.00002931342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002497612,"about_ca_system_score_gemma":0.0002449275,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9784598,"about_ca_topic_score_gemma":0.9765604,"domain_scores_codex":[0.9984716,0.0002243977,0.0002900466,0.0004142051,0.0001394678,0.000460294],"domain_scores_gemma":[0.9991062,0.0003497457,0.0001135224,0.0002162187,0.00007830749,0.0001359739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002749742,0.00001009828,0.9953098,0.00001946978,0.00005401742,0.00008635148,0.0005551243,0.002768463,0.0001806027,0.00003587019,0.00004689802,0.0006583523],"study_design_scores_gemma":[0.000544041,0.0005322713,0.8285177,0.00001807407,0.0000445034,0.0001878555,0.00007550743,0.1681669,0.0001204469,0.001258932,0.0003255213,0.000208289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957466,0.00216591,0.000735608,0.0005569831,0.0004313287,0.0001144291,0.00004822528,0.00001243252,0.0001885154],"genre_scores_gemma":[0.9978933,0.00009823702,0.001299208,0.0001054408,0.0001336841,9.190396e-7,0.0001273,0.000005121785,0.0003368104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1667921,"threshold_uncertainty_score":0.839754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256523574603311,"score_gpt":0.2166506694398824,"score_spread":0.1940854336938493,"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."}}