{"id":"W2803355538","doi":"10.2981/wlb.2003.009","title":"The need to improve our attention to scale of resolution in grouse research","year":2003,"lang":"en","type":"article","venue":"Wildlife Biology","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; University of New Brunswick","keywords":"Scale (ratio); Spatial ecology; Temporal scales; Field (mathematics); Grouse; Ecology; Environmental resource management; Geography; Data science; Computer science; Environmental science; Cartography; Habitat; Biology; Mathematics","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":[0.001573221,0.00007051339,0.0001017327,0.00008172465,0.0001260199,0.00001175828,0.0002245028,0.00005856407,0.00001912289],"category_scores_gemma":[0.0001811991,0.00004877024,0.0000291524,0.0004544779,0.00007540826,0.00003617814,0.0001826473,0.0001008857,0.00033847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001092058,"about_ca_system_score_gemma":0.000006626324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007246558,"about_ca_topic_score_gemma":0.001019234,"domain_scores_codex":[0.9986786,0.0003176612,0.0002049703,0.0002640184,0.0001634333,0.0003712967],"domain_scores_gemma":[0.9995589,0.00004925695,0.00003161588,0.0002657067,0.00001134964,0.00008315007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001502089,0.0001777364,0.8366657,0.00000793065,0.00001028756,0.000002402625,0.0004660217,0.0005604161,0.0557641,0.004223814,0.08231629,0.01965513],"study_design_scores_gemma":[0.0005176916,0.0005367098,0.548328,0.00001750405,0.00000352693,0.000001187256,0.00112455,0.000143597,0.0004839941,0.0014719,0.4472222,0.0001490757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824896,0.00002075291,0.0004495401,0.01041404,0.0002427077,0.0005037129,0.000003184052,0.00001077908,0.005865638],"genre_scores_gemma":[0.997065,0.00002308557,0.0003799429,0.0007867913,0.00003958116,0.00006158484,0.000002132479,0.000006313167,0.001635578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3649059,"threshold_uncertainty_score":0.4350461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520130943119553,"score_gpt":0.3083416251506969,"score_spread":0.2831403157195013,"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."}}