{"id":"W2162126224","doi":"10.3389/fevo.2014.00052","title":"Process models and model-data fusion in dendroecology","year":2014,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Agence Nationale de la Recherche; Fonds de recherche du Québec – Nature et technologies; Labex OT-Med","keywords":"Dendroclimatology; Dendrochronology; Tree (set theory); Bayesian probability; Data assimilation; Climate change; Computer science; Climatology; Econometrics; Geography; Meteorology; Artificial intelligence; Mathematics; Ecology; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005205831,0.00008449092,0.0001739332,0.0002090625,0.00008304238,0.000008989765,0.0001370572,0.0001660985,0.00001162165],"category_scores_gemma":[0.0001104535,0.00008047825,0.000005773853,0.0001077536,0.0001377322,0.0003573298,0.00003586746,0.0001338933,0.0000046833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001384488,"about_ca_system_score_gemma":0.00003973712,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002285937,"about_ca_topic_score_gemma":0.02129949,"domain_scores_codex":[0.9990715,0.0001449472,0.0001569549,0.0003118154,0.0000520775,0.0002627456],"domain_scores_gemma":[0.9996668,0.000100682,0.00004050681,0.0001334984,0.0000099641,0.0000486105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001284819,0.00001257915,0.930975,0.00001885481,0.000002372855,0.000002979393,0.0001270544,0.06046213,0.000002195855,0.00008629946,0.0002002713,0.007981738],"study_design_scores_gemma":[0.0002302754,0.00004221312,0.4930774,0.000004906302,0.000003032704,0.000008151574,0.00006914419,0.4925233,5.196054e-7,0.01397521,0.00001966575,0.00004625777],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931824,0.0007951322,0.004860012,0.0002274193,0.000283304,0.0001156023,0.00002427056,0.00001752636,0.000494314],"genre_scores_gemma":[0.9964256,0.0003349932,0.003066648,0.00005996794,0.00001582373,0.000002243135,0.00005967644,0.000002150627,0.00003292232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4378977,"threshold_uncertainty_score":0.9965593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162932274869969,"score_gpt":0.2326067043514626,"score_spread":0.2163134768644657,"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."}}