{"id":"W1991881129","doi":"10.1139/x02-161","title":"FVSBGC: a hybrid of the physiological model STAND-BGC and the forest vegetation simulator","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thinning; Pinus contorta; Environmental science; Computer science; Tree (set theory); Forestry; Calibration; Simulation; Statistics; Mathematics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006801646,0.0008071408,0.0004308956,0.0003971906,0.0003521842,0.0007334715,0.00183431,0.0006349682,0.006287208],"category_scores_gemma":[0.001231422,0.0005264675,0.0006875893,0.0004119066,0.0002777602,0.000877965,0.0006281494,0.001207545,0.001455069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009353426,"about_ca_system_score_gemma":0.001725266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03844862,"about_ca_topic_score_gemma":0.03126642,"domain_scores_codex":[0.9998253,0.00002790792,0.00001326196,0.00004431783,0.00005889092,0.00003042198],"domain_scores_gemma":[0.9995695,0.0001356142,0.00002286504,0.00007218699,0.0001297697,0.00007008089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007248789,0.0004779945,0.01901466,0.0004177576,0.0002871173,0.0002416124,0.0002715501,0.828002,0.01775986,0.01129097,0.05218866,0.06932288],"study_design_scores_gemma":[0.0001975115,0.00008531122,0.002523651,0.00001377316,0.00003817316,0.00004212102,0.00001385298,0.9725555,0.004291915,0.001702377,0.01849314,0.00004268359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3113504,0.0004830928,0.4189747,0.0006326151,0.0007503403,0.0008385376,0.04074172,0.1763995,0.04982902],"genre_scores_gemma":[0.7792636,0.0002640143,0.1640204,0.0003111124,0.00008068095,0.0007939085,0.03380782,0.009641946,0.01181638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03844862,"threshold_uncertainty_score":0.07644969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02977437837953605,"score_gpt":0.2602868902581178,"score_spread":0.2305125118785817,"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."}}