{"id":"W2033296753","doi":"10.1111/j.1365-2699.2007.01785.x","title":"A pre‐European settlement pollen–climate calibration set for Minnesota, USA: developing tools for palaeoclimatic reconstructions","year":2007,"lang":"en","type":"article","venue":"Journal of Biogeography","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Minnesota Department of Natural Resources","keywords":"Tsuga; Pollen; Climate change; Climate pattern; Geography; Settlement (finance); Physical geography; Ecology; Environmental science; Biology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002757722,0.0006424197,0.0003967312,0.002913497,0.0007039554,0.0009911177,0.0008407607,0.0005934858,0.001417025],"category_scores_gemma":[0.007524648,0.0004383888,0.0006961464,0.001704318,0.0002445348,0.0007449641,0.001279393,0.0006838112,0.0005707518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008970453,"about_ca_system_score_gemma":0.001202842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02605183,"about_ca_topic_score_gemma":0.03532206,"domain_scores_codex":[0.9994532,0.0001691386,0.00005802346,0.0002042313,0.0000839634,0.00003134968],"domain_scores_gemma":[0.9977983,0.0008240585,0.0002521498,0.0004984325,0.0005397995,0.00008729033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002907148,0.0002814079,0.3281186,0.0001733904,0.0005527516,0.000292033,0.0008886604,0.3216459,0.01489983,0.00469477,0.008435193,0.3197268],"study_design_scores_gemma":[0.00003495512,0.00003398833,0.174714,0.00004958369,0.00004586979,0.00007250381,0.0002226149,0.8123327,0.003056845,0.002352432,0.007046266,0.00003814922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6782156,0.0002250687,0.2985522,0.0001902168,0.00001738255,0.0001664012,0.01644092,0.003142613,0.003049479],"genre_scores_gemma":[0.7491564,0.00009003482,0.2252352,0.00003998255,0.00001172492,0.000314505,0.02420231,0.0003029373,0.0006469636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02605183,"threshold_uncertainty_score":0.05180037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03516685601993096,"score_gpt":0.2705452312776422,"score_spread":0.2353783752577112,"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."}}