{"id":"W6903871442","doi":"10.13140/rg.2.2.11780.83846","title":"Resource Roads and Grizzly Bears in British Columbia and Alberta, Canada","year":2018,"lang":"en","type":"article","venue":"","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Grizzly Bears; Resource (disambiguation); Ursus; Resource management (computing)","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":[0.0005271125,0.0002845112,0.0004139596,0.001740395,0.004484434,0.002069302,0.001123202,0.0007839447,0.003875535],"category_scores_gemma":[0.001415259,0.0002883056,0.0004267547,0.00420299,0.00123326,0.000679815,0.001373923,0.0008952381,0.0003245695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01932236,"about_ca_system_score_gemma":0.02168067,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9977486,"about_ca_topic_score_gemma":0.9995295,"domain_scores_codex":[0.9993926,0.00005914555,0.00002176142,0.00007361612,0.0001075703,0.0003452153],"domain_scores_gemma":[0.9982322,0.0001520916,0.0002569057,0.00004695148,0.0007283777,0.0005835046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001604244,0.0000701268,0.9796881,0.00004145594,0.00009069485,0.0003580226,0.004135586,0.000440099,0.0001609056,0.0008034107,0.004488979,0.009562162],"study_design_scores_gemma":[0.000005909264,0.000008223595,0.9857918,0.00005731201,0.00003706479,0.00005333758,0.01154538,0.000189738,0.00002576134,0.00007223667,0.002202123,0.0000110804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912905,0.001614829,0.00005628639,0.0007277904,0.00003328332,0.0000159117,0.001235959,0.000005408806,0.005020097],"genre_scores_gemma":[0.9927257,0.001087419,0.00009268596,0.0001392438,0.00001093595,0.000009583377,0.000761132,0.000006376056,0.005166959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01932236,"threshold_uncertainty_score":0.1401942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003830246452689314,"score_gpt":0.1760293246444197,"score_spread":0.1721990781917304,"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."}}