{"id":"W212698334","doi":"","title":"Assessing cumulative human impacts on northern woodland caribou with traditional ecological knowledge and resource selection functions","year":2010,"lang":"en","type":"article","venue":"The Mathematics Enthusiast","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Environment; University of Montana","keywords":"Woodland caribou; Selection (genetic algorithm); Woodland; Geography; Human use; Resource (disambiguation); Ecology; Environmental resource management; Cumulative effects; Environmental science; Computer science; Biology; Habitat; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002772128,0.0004561743,0.0003318808,0.001564115,0.0003164052,0.0008441058,0.0005223714,0.0003994539,0.0007481049],"category_scores_gemma":[0.007774653,0.0002145845,0.0006323469,0.001264875,0.0005420008,0.0007083447,0.0006901113,0.0002341146,0.0001151655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196647,"about_ca_system_score_gemma":0.0008559602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1247974,"about_ca_topic_score_gemma":0.199748,"domain_scores_codex":[0.999207,0.0003425978,0.00005268283,0.0001786968,0.0001268635,0.00009223613],"domain_scores_gemma":[0.9941177,0.003566062,0.0009868277,0.0005149263,0.0004702334,0.0003442648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004548007,0.00005384533,0.9783467,0.000006825977,0.0001340801,0.00003353538,0.0001424377,0.01606442,0.000123025,0.00009335759,0.00003800937,0.004918377],"study_design_scores_gemma":[0.000003941929,0.0001171135,0.8998955,0.00000808421,0.00006240512,0.00005085926,0.0003291895,0.09883509,0.00015306,0.0003143546,0.0002183244,0.00001207265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987404,0.00003513358,0.0008591277,0.00001188882,6.442222e-7,0.000004032211,0.0001000046,0.000008266114,0.0002406375],"genre_scores_gemma":[0.9988381,0.00002343999,0.0007778323,0.000004388437,0.000001471613,0.000006433069,0.0002164101,0.000002048284,0.0001298515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1247974,"threshold_uncertainty_score":0.2481421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03361715662547467,"score_gpt":0.2636855006070998,"score_spread":0.2300683439816251,"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."}}