{"id":"W2013050145","doi":"10.1016/j.ecocom.2006.05.001","title":"Landscapes as gradients: The spatial structure of terrestrial ecosystem components in southern Ontario, Canada","year":2007,"lang":"en","type":"article","venue":"Ecological Complexity","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Ivey Foundation","keywords":"Ecosystem; Spatial ecology; Environmental science; Physical geography; Sampling (signal processing); Scale (ratio); Precipitation; Vegetation (pathology); Variance (accounting); Ecology; Spatial variability; Geography; Soil science; Statistics; Cartography; Mathematics; Biology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002802446,0.0001077918,0.0002056011,0.00001459776,0.0001806975,0.000005437869,0.0002536598,0.00007494635,0.003249516],"category_scores_gemma":[0.00007331353,0.00006822789,0.00003549204,0.00008770617,0.0001710581,0.00002555307,0.0001766467,0.0002166807,0.00002527231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004265156,"about_ca_system_score_gemma":0.0000379892,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9211847,"about_ca_topic_score_gemma":0.9999306,"domain_scores_codex":[0.9989446,0.000116202,0.0003030202,0.0001889216,0.0001919481,0.0002553225],"domain_scores_gemma":[0.9994459,0.0002548256,0.0001305903,0.0001147695,0.00000597384,0.00004798752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008436941,0.00007993919,0.997896,0.000002087823,0.00001257883,0.00001412412,0.0006748511,0.000638917,0.00008770285,0.0003183616,0.0001214906,0.00006962356],"study_design_scores_gemma":[0.0004609931,0.00007787252,0.9938982,0.000002664528,0.000005309861,0.000003774438,0.0003166832,0.0007167762,0.00001706543,0.003954178,0.0004674085,0.00007912055],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961403,0.000003039343,0.00002665615,0.0001684961,0.0003242778,0.000226889,0.00003683803,0.000008136321,0.003065366],"genre_scores_gemma":[0.9996188,3.31131e-7,0.00007702673,0.0001588522,0.00002542442,0.000002782064,0.00001841202,0.000002725526,0.0000956492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07874589,"threshold_uncertainty_score":0.9976617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366665839467765,"score_gpt":0.2240129837857742,"score_spread":0.2003463253910966,"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."}}