{"id":"W3157035310","doi":"10.1002/ecs2.3484","title":"Vegetation dynamics models: a comprehensive set for natural resource assessment and planning in the United States","year":2021,"lang":"en","type":"article","venue":"Ecosphere","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Baseline (sea); Environmental resource management; Vegetation (pathology); Context (archaeology); Ecosystem services; Ecosystem; Ecosystem management; Disturbance (geology); Variety (cybernetics); Resource (disambiguation); Land use; Land management; Adaptive management; Environmental science; Ecology; Geography; Computer science; Political 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":[0.0025481,0.000885737,0.0005924389,0.0021647,0.0007172809,0.001750931,0.001477244,0.0008323304,0.004344609],"category_scores_gemma":[0.005731757,0.0007492119,0.001183643,0.002305049,0.0002936404,0.001564382,0.001097012,0.0008196454,0.001045366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590447,"about_ca_system_score_gemma":0.003303595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07465966,"about_ca_topic_score_gemma":0.103484,"domain_scores_codex":[0.9991572,0.0004051007,0.0000790914,0.00008294702,0.0002330714,0.00004262391],"domain_scores_gemma":[0.9969133,0.001366127,0.0002851502,0.0005659006,0.0007256776,0.0001438375],"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":[0.00006161694,0.0001823139,0.01062695,0.0001803434,0.0001470939,0.0001073274,0.0001147154,0.8680853,0.0004215121,0.01421317,0.04700482,0.05885493],"study_design_scores_gemma":[0.0000580202,0.00003634251,0.003450804,0.0001752576,0.00004738086,0.00003681656,0.0001146814,0.9368842,0.0004706456,0.01275024,0.04593604,0.0000396663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1625008,0.00193141,0.4884929,0.003192123,0.0001930274,0.00146509,0.2292009,0.01737877,0.09564497],"genre_scores_gemma":[0.4606408,0.001745055,0.4156455,0.0004610659,0.0000568837,0.002234846,0.1112343,0.00133372,0.006647934],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07465966,"threshold_uncertainty_score":0.1484501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02291120849753836,"score_gpt":0.2722511065857421,"score_spread":0.2493398980882037,"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."}}