{"id":"W2162026527","doi":"10.1023/a:1012537914881","title":"Comparing the Performance of Forest gap Models in North America","year":2001,"lang":"en","type":"article","venue":"Climatic Change","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"U.S. Department of Energy; National Science Foundation","keywords":"Environmental science; Temperate climate; Temperate forest; Ecological succession; Taiga; Boreal; Biomass (ecology); Temperate rainforest; Climate change; Ecology; Precipitation; Forest ecology; Physical geography; Atmospheric sciences; Ecosystem; Geography; Biology; Meteorology; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006957391,0.00005075919,0.0000864618,0.00001835004,0.00003506783,0.000005410873,0.0001323096,0.00001343238,0.00006584702],"category_scores_gemma":[0.000001846348,0.00003477943,0.0000172279,0.0002080459,0.00006738847,0.0001288411,0.00007658529,0.00005446918,0.00005074458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003695846,"about_ca_system_score_gemma":0.000001127346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003378398,"about_ca_topic_score_gemma":0.00348759,"domain_scores_codex":[0.9995534,0.00001220926,0.0001298185,0.00007237671,0.0001037343,0.0001284446],"domain_scores_gemma":[0.9997717,0.0000196328,0.00005180778,0.0001372362,0.000001584129,0.00001808479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002923388,0.00002131481,0.8896602,0.000007702544,0.000001055775,0.000001116131,0.001349663,0.1077284,0.000007156961,0.0000274814,0.000004690861,0.001188375],"study_design_scores_gemma":[0.00005750508,0.00001125202,0.3484464,0.000009936175,0.000002447245,0.000002812501,0.00003726402,0.6512306,7.604892e-7,0.0000837732,0.00008641469,0.00003083622],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920697,0.00001923417,0.0001377562,0.00006738958,0.00001981872,0.0001357629,0.000002780273,0.000006536821,0.007541063],"genre_scores_gemma":[0.9995297,0.0001750584,0.0001312009,0.00006350029,0.00000751529,0.00002481537,0.00001112616,0.000003707211,0.00005336543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5435022,"threshold_uncertainty_score":0.1946157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05833549959038756,"score_gpt":0.2256601554078431,"score_spread":0.1673246558174555,"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."}}