{"id":"W2019841367","doi":"10.1657/1938-4246.46.1.55","title":"Holocene Climate and Environmental Changes in Western Subarctic Québec as Inferred from the Sedimentology and the Geomorphology of a Lake Watershed","year":2014,"lang":"en","type":"article","venue":"Arctic Antarctic and Alpine Research","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Center for Northern Studies","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subarctic climate; Sedimentology; Geology; Holocene; Holocene climatic optimum; Peat; Bay; Paleolimnology; Physical geography; Climate change; Stratigraphy; Oceanography; Geomorphology; Ecology; Paleontology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002106815,0.0001662492,0.0001283142,0.001159176,0.001032369,0.0009959143,0.000402589,0.0002467337,0.002227334],"category_scores_gemma":[0.0005986599,0.0001221767,0.0001461209,0.002228963,0.0004794238,0.0003238379,0.0003146368,0.0002497044,0.0001578721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01846501,"about_ca_system_score_gemma":0.007204384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926037,"about_ca_topic_score_gemma":0.9966006,"domain_scores_codex":[0.9998719,0.00001276162,0.000005300803,0.00002781197,0.00002609769,0.0000561544],"domain_scores_gemma":[0.9996095,0.00002806656,0.00007918579,0.00001191117,0.000172676,0.00009860094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007360332,0.00003206534,0.979838,0.00002650602,0.00006869737,0.0002838572,0.00112242,0.0008464894,0.001547632,0.0002939585,0.001511922,0.0143548],"study_design_scores_gemma":[0.000002323349,0.000002776939,0.9981371,0.000007578315,0.000006024778,0.0000183039,0.0003459753,0.0004237325,0.00003268449,0.00001106879,0.001008878,0.000003472678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957647,0.0003864227,0.00009268834,0.0001581147,0.000003779007,0.000009883448,0.001627098,0.00001633435,0.001940974],"genre_scores_gemma":[0.9977507,0.0001865656,0.0001461106,0.00003499792,0.000002141061,0.000007648671,0.0009041604,0.000004563365,0.0009632217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01846501,"threshold_uncertainty_score":0.1339737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973419542516116,"score_gpt":0.2577361413018137,"score_spread":0.2380019458766525,"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."}}