{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005079012,0.00003129857,0.00004716124,0.000005373171,0.00009277014,0.0001010325,0.00003754915,0.00002159651,0.002587951],"category_scores_gemma":[0.00002055926,0.00004699893,0.000004136144,0.00007719941,0.00009367882,0.0001310932,0.00005324199,0.00004087701,0.00001259799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006553177,"about_ca_system_score_gemma":0.00001452356,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9986981,"about_ca_topic_score_gemma":0.9999504,"domain_scores_codex":[0.9995651,0.00001433618,0.00008649763,0.000152391,0.00007856789,0.0001030946],"domain_scores_gemma":[0.9998347,0.00002806022,0.00001673111,0.00006671176,0.000003172407,0.00005067631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001353298,0.000006960786,0.8817923,6.59784e-7,0.000001169996,0.000002529742,0.00006229067,0.000001233264,0.00007573356,0.000003178048,0.1032037,0.01484888],"study_design_scores_gemma":[0.00009338784,0.00002168406,0.8398793,0.000006599252,0.000001240508,0.00002407736,0.0001646671,0.0004760806,0.00001126015,0.0000272327,0.1592392,0.00005533413],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678443,0.000006397246,0.000003355162,0.0007066609,0.00003176588,0.00005607704,0.000001576099,0.000004331752,0.03134552],"genre_scores_gemma":[0.9779164,0.000005751515,0.0001363132,0.001523336,0.00001642864,0.000002797239,0.000001745669,0.000003548953,0.02039364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05603544,"threshold_uncertainty_score":0.9983238,"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."}}