{"id":"W3176856469","doi":"10.3390/rs13132547","title":"Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (Ursus Arctos) Habitat","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; fRI Research; Shell Canada","keywords":"Ursus; Grizzly Bears; Habitat; Geography; Context (archaeology); Environmental resource management; Global Positioning System; Environmental science; Cartography; Ecology; Computer science; Population","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":[0.0002964982,0.0002190693,0.0002296712,0.00006278983,0.0004451223,0.000312272,0.0001355184,0.0001018251,0.00001955548],"category_scores_gemma":[0.0002387066,0.000221228,0.00003194483,0.0003841517,0.0001201745,0.0008928043,0.0002502401,0.0002195486,0.00007316769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001953383,"about_ca_system_score_gemma":0.0000390875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773416,"about_ca_topic_score_gemma":0.005905363,"domain_scores_codex":[0.9980406,0.0001325028,0.0002867805,0.0007752063,0.000429352,0.0003355543],"domain_scores_gemma":[0.9987796,0.00010364,0.0001612002,0.0006889946,0.00008281178,0.0001837489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006740588,0.00001493335,0.0003860103,0.000006777657,0.00001715057,0.0000395054,0.001605101,0.00004918853,0.3178559,0.000003884732,0.0003164112,0.6796378],"study_design_scores_gemma":[0.001082245,0.0001357259,0.3250185,0.0003180954,0.0001598852,0.0007472811,0.00198094,0.58042,0.01676277,0.0001502531,0.07203447,0.001189809],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719132,0.00001093627,0.02446974,0.002756812,0.0001620232,0.0002065068,0.00001675748,0.00009612741,0.0003678537],"genre_scores_gemma":[0.9351094,0.0000185459,0.06258611,0.001469852,0.0003541204,3.042051e-8,0.000262184,0.00005058474,0.0001491813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.678448,"threshold_uncertainty_score":0.9021414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02800405922688556,"score_gpt":0.2532257668902596,"score_spread":0.225221707663374,"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."}}