{"id":"W2077116226","doi":"10.1007/s10531-010-9852-7","title":"Intra-specific niche partitioning obscures the importance of fine-scale habitat data in species distribution models","year":2010,"lang":"en","type":"article","venue":"Biodiversity and Conservation","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University; Acadia University","funders":"","keywords":"Habitat; Riparian zone; Elevation (ballistics); Niche; Ecology; Land cover; Geography; Environmental niche modelling; Scale (ratio); Physical geography; Geographic information system; Field (mathematics); Ecological niche; Biodiversity; Environmental science; Species distribution; Land use; Cartography; Biology","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":[0.01426359,0.0007636004,0.001600664,0.001090784,0.001363392,0.001875115,0.002249942,0.001430972,0.002791728],"category_scores_gemma":[0.0629215,0.001113416,0.001482474,0.001653522,0.002625488,0.005719566,0.002794548,0.002613086,0.0004552221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000662216,"about_ca_system_score_gemma":0.0007088296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005440921,"about_ca_topic_score_gemma":0.009662314,"domain_scores_codex":[0.9952621,0.00337228,0.0002034651,0.0007335197,0.0002611203,0.0001674653],"domain_scores_gemma":[0.9492726,0.03994022,0.001318019,0.007939748,0.0007977731,0.0007316401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001320629,0.0004311491,0.209922,0.0006156331,0.001794971,0.0004707802,0.001451024,0.5686337,0.008768535,0.09400877,0.003334743,0.109248],"study_design_scores_gemma":[0.00009325557,0.0001159191,0.04125503,0.00006043376,0.0002000599,0.0005831495,0.0002242263,0.8090959,0.00111627,0.1454279,0.001773384,0.00005433431],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.695962,0.0005676752,0.2913639,0.001335803,0.00007320983,0.00009310972,0.0007796938,0.0004635475,0.009361137],"genre_scores_gemma":[0.980534,0.0001136385,0.0182203,0.000216529,0.00004186488,0.00004701356,0.0002445452,0.0001586941,0.0004234482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01426359,"threshold_uncertainty_score":0.07543397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03765916494999048,"score_gpt":0.2080859499659286,"score_spread":0.1704267850159381,"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."}}