{"id":"W3022890307","doi":"10.1002/ecs2.3109","title":"Capturing ecological processes in dynamic forest models: why there is no silver bullet to cope with complexity","year":2020,"lang":"en","type":"article","venue":"Ecosphere","topic":"Forest ecology and management","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western Forest Products; University of British Columbia","funders":"Staatssekretariat für Bildung, Forschung und Innovation","keywords":"Overfitting; Computer science; Forest dynamics; Set (abstract data type); Ecology; Process (computing); Range (aeronautics); Temporal scales; Machine learning; Artificial neural network; Engineering","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":[0.01224931,0.001298931,0.002014023,0.001447013,0.0007375836,0.003476527,0.00370788,0.002464902,0.001971352],"category_scores_gemma":[0.06482606,0.001093604,0.00191757,0.001557859,0.003891921,0.01279118,0.004194782,0.005482955,0.0005983955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229867,"about_ca_system_score_gemma":0.00158572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007638196,"about_ca_topic_score_gemma":0.006874024,"domain_scores_codex":[0.9956787,0.002459856,0.0002162922,0.0005874422,0.0008571682,0.0002005553],"domain_scores_gemma":[0.9676253,0.02208073,0.001756138,0.005687018,0.001884883,0.0009659181],"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":[0.000223486,0.0001672475,0.01800443,0.0004926209,0.0005724228,0.0001393538,0.0006919816,0.8090479,0.001919482,0.1050524,0.006443442,0.05724517],"study_design_scores_gemma":[0.00003905589,0.00009019857,0.001657175,0.0002001685,0.00006480583,0.0000740617,0.0001668521,0.771274,0.0004675878,0.2211706,0.004737597,0.00005793135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1257487,0.003254631,0.8419665,0.02149634,0.0004139137,0.0001375341,0.0004549956,0.001181204,0.005346064],"genre_scores_gemma":[0.7202139,0.002024602,0.2715449,0.002597136,0.0004655518,0.0002677532,0.0003193853,0.000965616,0.001601105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01224931,"threshold_uncertainty_score":0.06478131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01989146935982897,"score_gpt":0.2079644798829904,"score_spread":0.1880730105231614,"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."}}