{"id":"W2800466929","doi":"10.1139/cjb-2017-0182","title":"Vegetation and climate history of Quebec’s mixed boreal forest suggests greater abundance of temperate species during the early- and mid-Holocene","year":2018,"lang":"en","type":"article","venue":"Botany","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Center for Northern Studies","funders":"","keywords":"Macrofossil; Ecology; Temperate climate; Disjunct; Taiga; Boreal; Temperate rainforest; Tundra; Peat; Vegetation (pathology); Habitat; Temperate forest; Holocene; Range (aeronautics); Abundance (ecology); Climate change; Abies balsamea; Subarctic climate; Biology; Pollen; Geography; Arctic; Balsam; Ecosystem; Botany; Archaeology; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001630628,0.0001510566,0.0001007177,0.0008208053,0.001425911,0.000725613,0.0003023997,0.0001484282,0.003694895],"category_scores_gemma":[0.0002834209,0.00009753816,0.000109908,0.0009653515,0.000361488,0.0002389462,0.0002015394,0.0001863686,0.0001455534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008062472,"about_ca_system_score_gemma":0.00395312,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9816197,"about_ca_topic_score_gemma":0.9962347,"domain_scores_codex":[0.9999182,0.000006042717,0.000002327224,0.00002478348,0.00001806832,0.00003042373],"domain_scores_gemma":[0.9996923,0.0000231005,0.00006117409,0.00001098217,0.0001253139,0.00008712878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007613161,0.00003348598,0.9814616,0.0000237099,0.00005038437,0.0001281894,0.0008273495,0.00029805,0.002957084,0.0002797967,0.001049642,0.01281469],"study_design_scores_gemma":[0.00000148889,0.00000495386,0.9985191,0.000005036485,0.000004327746,0.00002384809,0.0002725217,0.0001584231,0.0000498067,0.000008733952,0.0009498186,0.000002056154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938182,0.0004089954,0.0001427197,0.0001115527,0.000005490256,0.000009250385,0.001287288,0.000009610516,0.004206913],"genre_scores_gemma":[0.9983205,0.0001034152,0.0001044505,0.00002887834,0.000002133873,0.000003016823,0.0004433978,0.000002129299,0.0009920318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01838028,"threshold_uncertainty_score":0.05849755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488228280757126,"score_gpt":0.2141846536090804,"score_spread":0.1993023708015091,"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."}}