{"id":"W2964944471","doi":"10.1002/ecy.2856","title":"Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States","year":2019,"lang":"en","type":"article","venue":"Ecology","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University","funders":"Division of Environmental Biology; University of Notre Dame; National Science Foundation","keywords":"Ecology; Ecotone; Range (aeronautics); Tsuga; Climate change; Vegetation (pathology); Geography; Temperate rainforest; Fraxinus; Abundance (ecology); Physical geography; Temperate forest; Forest dynamics; Ecosystem; Biology; Habitat","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004701986,0.00006700668,0.0001339285,0.0003264459,0.00007075974,0.0000101519,0.0001324643,0.0001131954,0.0006778415],"category_scores_gemma":[0.00001349755,0.00004735392,0.00001273708,0.0003245802,0.0001302977,0.00006191537,0.00001008298,0.0002444522,0.000157427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002661642,"about_ca_system_score_gemma":0.00001431435,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478165,"about_ca_topic_score_gemma":0.2069016,"domain_scores_codex":[0.998947,0.0004303565,0.000130308,0.0001652814,0.00005344413,0.0002735928],"domain_scores_gemma":[0.9990948,0.0007477867,0.00002933788,0.00009460678,0.00001015106,0.00002330635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006503754,0.00001714779,0.9911778,0.00001168729,0.000003426473,0.00003182261,0.0008650807,0.007389761,0.000001051532,0.0001147699,0.00003940338,0.0002830209],"study_design_scores_gemma":[0.0004089639,0.0001676782,0.9783173,0.000004683162,0.000002155248,0.00005398581,0.0003048905,0.01963128,3.93545e-7,0.000351889,0.000703007,0.00005374471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959393,0.0002234386,5.141224e-7,0.001951922,0.0001631691,0.0001116482,0.000005166193,0.00000654016,0.001598334],"genre_scores_gemma":[0.9990399,0.00006062497,0.00001389238,0.0004153913,0.000008809818,0.000003080795,0.000310381,0.000001064464,0.000146813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2054234,"threshold_uncertainty_score":0.8075704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02700755001721052,"score_gpt":0.2680829628107859,"score_spread":0.2410754127935754,"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."}}