{"id":"W4220945989","doi":"10.1002/essoar.10510735.1","title":"A framework for 210Pb model selection and its application to 37 cores from Eastern Canada to identify the dynamics and drivers of lake sedimentation rates","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Université du Québec à Montréal; Université de Sherbrooke; Université Laval; McGill University; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Limnology; Library science; World Wide Web; Geography; Computer science; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006443787,0.001120942,0.0006277104,0.001940446,0.001754832,0.001286936,0.002143371,0.0006742997,0.002094038],"category_scores_gemma":[0.01085442,0.0007551807,0.001124267,0.001489944,0.0007156142,0.0003953213,0.001341125,0.00108252,0.0002519017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003292258,"about_ca_system_score_gemma":0.006756222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4273959,"about_ca_topic_score_gemma":0.4077383,"domain_scores_codex":[0.9988536,0.0006019693,0.00006861504,0.0001789375,0.0002028095,0.00009414884],"domain_scores_gemma":[0.9961825,0.00248929,0.0002454796,0.0001156762,0.0008893325,0.00007774518],"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":[0.00008897546,0.00007901026,0.02686966,0.00008573612,0.0002187391,0.0002719449,0.0004597234,0.8981403,0.00157247,0.0266824,0.002214101,0.04331699],"study_design_scores_gemma":[0.00001667838,0.00001472899,0.002150623,0.00001168232,0.00001890692,0.00001793512,0.00007346048,0.9927931,0.0002100632,0.003471333,0.00120976,0.000011775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06626894,0.0001327184,0.929414,0.0001997483,0.00001242488,0.0003351146,0.0008560614,0.000863183,0.001917765],"genre_scores_gemma":[0.2897719,0.0001358483,0.7050071,0.0000809816,0.00001803747,0.0008468031,0.002141314,0.0002839508,0.00171409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5726041,"threshold_uncertainty_score":0.8498164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131246547557001,"score_gpt":0.273856002812741,"score_spread":0.260731348057041,"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."}}