{"id":"W2040926197","doi":"10.1111/j.1472-4642.2007.00342.x","title":"Sensitivity of predictive species distribution models to change in grain size","year":2007,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":545,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bird Studies Canada","keywords":"Grain size; Species distribution; Biodiversity; Sample size determination; Ranking (information retrieval); Ecology; Sensitivity (control systems); Statistics; Biological system; Environmental science; Econometrics; Mathematics; Biology; Habitat; Computer science; Materials science; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009858985,0.0008442659,0.0008580961,0.0007793742,0.0004269736,0.001460319,0.0008484012,0.001018255,0.0005764189],"category_scores_gemma":[0.03061564,0.0005893144,0.00108146,0.000607803,0.0008872346,0.00173232,0.001465218,0.001374796,0.0001534454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101636,"about_ca_system_score_gemma":0.0005774656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01346529,"about_ca_topic_score_gemma":0.005188209,"domain_scores_codex":[0.9979417,0.001053942,0.0001611446,0.0004151168,0.0002721314,0.0001558823],"domain_scores_gemma":[0.9607512,0.03376961,0.001581896,0.002484425,0.001035108,0.0003777102],"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":[0.0003660645,0.00005025835,0.02210697,0.00003666933,0.0001731607,0.00003792083,0.00005012127,0.9681578,0.002609836,0.0002141901,0.0001209208,0.00607605],"study_design_scores_gemma":[0.00002047474,0.0001329957,0.009617796,0.00001484771,0.00004657982,0.00003052318,0.00003631122,0.985984,0.003095725,0.000850197,0.0001462184,0.00002429724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966277,0.0003586379,0.03146703,0.0002937111,0.00003893462,0.00004055694,0.0003145377,0.0004563361,0.0007532649],"genre_scores_gemma":[0.9952632,0.00004470819,0.004248462,0.00003687316,0.000005521885,0.00001708967,0.0002651153,0.00002498575,0.00009401589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01346529,"threshold_uncertainty_score":0.05213988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04934278090149152,"score_gpt":0.2412059781241939,"score_spread":0.1918631972227024,"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."}}