{"id":"W4391830674","doi":"10.1016/j.biocon.2024.110489","title":"Temporal dynamics in gray wolf space use suggest stabilizing range in the Great Lakes region, USA","year":2024,"lang":"en","type":"article","venue":"Biological Conservation","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University; Ministry of Natural Resources and Forestry","funders":"U.S. Fish and Wildlife Service; Michigan State University","keywords":"Ecology; Gray wolf; Habitat; Disturbance (geology); Canis; Range (aeronautics); Geography; Population; Species distribution; Biology; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007530001,0.000125393,0.0001241518,0.0000526711,0.00008585059,0.00006940286,0.0001753416,0.0001882815,0.0002037634],"category_scores_gemma":[0.0003635551,0.00008077399,0.00003793699,0.0006016995,0.00023515,0.0003847223,0.00005576407,0.0002376107,0.0001031675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002724876,"about_ca_system_score_gemma":0.00001866838,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002607848,"about_ca_topic_score_gemma":0.06085219,"domain_scores_codex":[0.9987217,0.0003642252,0.0002563579,0.0003255054,0.000116143,0.0002161384],"domain_scores_gemma":[0.9990823,0.0006729013,0.00004841608,0.0001634091,0.000008222704,0.00002471006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003381146,0.00003734679,0.9932113,0.000004926313,0.000001714782,0.00004536036,0.0001969326,0.00003222639,0.00007088957,0.004162392,0.001687744,0.0005153716],"study_design_scores_gemma":[0.0001486244,0.00006598085,0.9830214,0.00002359951,0.000003345194,0.00001081986,0.0002294792,0.006952309,0.000003556003,0.001970788,0.007457245,0.0001128495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983522,0.00005369455,0.0001870412,0.01523892,0.0001192108,0.000336643,0.000005146727,0.00004813585,0.0004891942],"genre_scores_gemma":[0.9970812,0.00004816372,0.000166936,0.002272355,0.00002530554,0.00006727249,0.00007048058,0.000005207732,0.0002630492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05824435,"threshold_uncertainty_score":0.9562848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05164449706150685,"score_gpt":0.2515265012641509,"score_spread":0.1998820042026441,"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."}}