{"id":"W1965312634","doi":"10.1002/jwmg.435","title":"Keep in touch: Does spatial overlap correlate with contact rate frequency?","year":2012,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Home range; Range (aeronautics); Correlation; Intraspecific competition; Statistics; Proxy (statistics); Context (archaeology); Index (typography); Wildlife; Ecology; Demography; Biology; Mathematics; Materials science; Computer science; Habitat","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":[0.0007658287,0.0001429395,0.0002120969,0.00009932905,0.0000704599,0.00002278988,0.0002144689,0.00006184809,0.0009064542],"category_scores_gemma":[0.0000246826,0.00009528092,0.00005673014,0.0001867683,0.00006695135,0.0006835175,0.00009066122,0.0002352572,0.0001568691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002423512,"about_ca_system_score_gemma":0.00001197271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002088705,"about_ca_topic_score_gemma":0.0003734251,"domain_scores_codex":[0.9986736,0.000121826,0.0004326902,0.0001320366,0.0003104828,0.0003294211],"domain_scores_gemma":[0.9992695,0.00005976884,0.0003814625,0.0001552504,0.00001250393,0.0001215574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001580679,0.000183451,0.9918349,0.000008876077,0.00006401107,0.0001073906,0.0002785338,0.0006043052,0.00005079152,0.0004906047,0.003881229,0.002337787],"study_design_scores_gemma":[0.001139476,0.0002026277,0.9880918,0.00005190086,0.00005971796,0.00002815905,0.0002647654,0.0001050327,0.00001992351,0.0005504838,0.009343674,0.000142437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98525,0.00002485898,0.00119231,0.002661213,0.0007005074,0.0002091472,9.94578e-7,0.000009237964,0.00995172],"genre_scores_gemma":[0.9938822,0.0000614426,0.001177967,0.003993789,0.0001533962,0.000008056384,0.000001307078,0.00001124905,0.0007105812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009241139,"threshold_uncertainty_score":0.9925038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006674031802234608,"score_gpt":0.2017733713487295,"score_spread":0.1950993395464949,"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."}}