{"id":"W4387399575","doi":"10.1007/s10980-023-01771-2","title":"Effects of sample size, data quality, and species response in environmental space on modeling species distributions","year":2023,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Species distribution; Linear discriminant analysis; Skewness; Sample size determination; Statistics; Random forest; Kurtosis; Principle of maximum entropy; Generalized additive model; Linear regression; Mathematics; Ecology; Biology; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005075329,0.000122265,0.0002223818,0.00005117081,0.00009628789,0.00001459087,0.0002507727,0.00008478653,0.009553134],"category_scores_gemma":[0.0009723147,0.0001159916,0.0000279846,0.00024877,0.0001998116,0.00008909747,0.000686362,0.0001050498,0.0003479757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001812729,"about_ca_system_score_gemma":0.000006370227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007280122,"about_ca_topic_score_gemma":0.0008166892,"domain_scores_codex":[0.9987577,0.0001791199,0.0002296772,0.0003506079,0.0001774983,0.000305434],"domain_scores_gemma":[0.997606,0.001923054,0.00006390617,0.000338126,0.000002019163,0.0000668689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007637699,0.0004285453,0.9507751,0.00004578395,0.00002152466,0.00004126035,0.000533897,0.001432018,0.03109267,0.002532255,0.01221975,0.0001134502],"study_design_scores_gemma":[0.0006640415,0.0001325956,0.9902583,0.00000599652,0.000008013675,0.000002285603,0.001170993,0.003525487,0.0005512959,0.0003561433,0.003200402,0.0001244876],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948595,0.00002328836,0.00005514356,0.001442522,0.0001136492,0.0001777634,0.001437389,0.00003541277,0.001855342],"genre_scores_gemma":[0.9985784,0.0003182689,0.0000396326,0.00008560865,0.00001884149,0.00001594606,0.0004689227,0.000008069555,0.0004663478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03948318,"threshold_uncertainty_score":0.9913523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05542777072839829,"score_gpt":0.2913556015390754,"score_spread":0.2359278308106771,"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."}}