{"id":"W2398444803","doi":"10.1002/ece3.2154","title":"Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow","year":2016,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Montana","keywords":"Resistance (ecology); Computer science; Gene flow; Landscape connectivity; Ecology; Gene; Biology; Biological dispersal; Genetics; Genetic variation; Medicine; Population; Environmental health","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":[],"consensus_categories":[],"category_scores_codex":[0.0003872689,0.00006730637,0.00008108895,0.00005908373,0.0003042996,0.00001824875,0.0000455343,0.00005567568,0.0003418295],"category_scores_gemma":[0.0002417278,0.00005476116,0.00002190378,0.0001423765,0.00002886544,0.0002316976,0.00003250922,0.00002624654,0.00004712892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002175952,"about_ca_system_score_gemma":0.00002041549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002079363,"about_ca_topic_score_gemma":0.0004877516,"domain_scores_codex":[0.9993237,0.0001082907,0.0001365262,0.0002201524,0.00005005936,0.0001612844],"domain_scores_gemma":[0.9995104,0.0002492963,0.00004489802,0.0001089481,0.00002719906,0.00005926333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000235867,0.00007620849,0.3587036,0.000009232352,0.00001899732,6.210002e-7,0.000135876,0.08032559,0.5335333,0.0002741774,0.004993504,0.02169307],"study_design_scores_gemma":[0.0003402827,0.00005416194,0.6996782,0.00002033615,0.00002403672,0.000001898232,0.0000172686,0.2909243,0.001578059,0.001310501,0.005940329,0.0001107206],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5048818,0.000005809016,0.4930166,0.001667921,0.0001359037,0.0001552625,0.00000609396,0.00001169624,0.000118925],"genre_scores_gemma":[0.728973,5.386518e-7,0.2701361,0.0004309916,0.00003461017,0.00003148093,0.000003450828,0.000004901096,0.000384857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5319552,"threshold_uncertainty_score":0.3742794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0470383198343571,"score_gpt":0.3722504895476955,"score_spread":0.3252121697133384,"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."}}