{"id":"W6948515598","doi":"10.5061/dryad.t5800","title":"Data from: Compensatory selection for roads over natural linear features by wolves in northern Ontario: implications for caribou conservation","year":2017,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Musicology and Musical Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas; University of Guelph; Trent University","funders":"","keywords":"Woodland caribou; Selection (genetic algorithm); Woodland; Habitat; Range (aeronautics); Threatened species; Predation; Linear model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003908363,0.0003740824,0.0005801048,0.0001104837,0.001284714,0.0004166103,0.002114742,0.0002088333,0.00009296378],"category_scores_gemma":[0.00003714076,0.0003250761,0.00007730402,0.00003699868,0.0002338638,0.0005847568,0.000799839,0.0005411585,0.000003653153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005393549,"about_ca_system_score_gemma":0.00012693,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3540021,"about_ca_topic_score_gemma":0.9980156,"domain_scores_codex":[0.997979,0.0001019012,0.0004265265,0.0009978121,0.0001202546,0.0003744641],"domain_scores_gemma":[0.9968307,0.0007690254,0.0004489773,0.001783079,0.00008546795,0.00008273321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001774873,0.00009415555,0.01044472,0.0001871161,0.0003621346,3.898645e-7,0.001429227,0.00001539009,0.00001382514,0.00007976124,0.9864823,0.0007135373],"study_design_scores_gemma":[0.0005167447,0.00004055848,0.03965516,0.0001864167,0.000583547,0.000001011618,0.0001303102,0.01445484,2.906815e-7,0.0004306709,0.9436314,0.0003690211],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03142633,0.0005938564,0.00009445036,0.0003706671,0.0006244291,0.0005991295,0.9662085,0.00003367905,0.00004894373],"genre_scores_gemma":[0.005567963,0.000109915,0.0001968631,0.001015533,0.001460907,0.0001218502,0.9907954,0.00002742638,0.000704111],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6440135,"threshold_uncertainty_score":0.9999201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05297547023300987,"score_gpt":0.3016563057813945,"score_spread":0.2486808355483846,"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."}}