{"id":"W2758426069","doi":"10.1111/tgis.12295","title":"Northern marine transportation corridors: Creation and analysis of northern marine traffic routes in Canadian waters","year":2017,"lang":"en","type":"article","venue":"Transactions in GIS","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Canadian Hydrographic Service","funders":"Natural Resources Canada; Fisheries and Oceans Canada; Government of Canada; Aboriginal Affairs and Northern Development Canada; Transport Canada","keywords":"Arctic; Coast guard; Geography; Government (linguistics); Hydrography; The arctic; Environmental resource management; Environmental planning; Business; Fishery; Environmental protection; Oceanography; Environmental science; Cartography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002341541,0.00008556426,0.0002191796,0.0004326233,0.0005098493,0.00002729517,0.0001166458,0.00007013766,0.0001807306],"category_scores_gemma":[0.00002798868,0.00008273539,0.00006578384,0.0003604416,0.0003148579,0.0001831486,0.000001977195,0.00008685593,0.000001632949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001943115,"about_ca_system_score_gemma":0.0001497437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9657153,"about_ca_topic_score_gemma":0.9997856,"domain_scores_codex":[0.9992087,0.00004430557,0.0002321538,0.0001562746,0.0001251145,0.0002334508],"domain_scores_gemma":[0.9995902,0.00004338476,0.00008461889,0.0001454816,0.00004333369,0.000093018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000145137,0.00003207276,0.9175843,0.00000767549,0.00011586,0.00000353375,0.03338487,0.003283932,0.000001486246,0.0001009047,0.000001397422,0.04546944],"study_design_scores_gemma":[0.0002450903,0.00001307902,0.9938707,0.00001047034,0.0002031282,1.079858e-7,0.003701893,0.00107745,0.000004805973,0.0001078734,0.0006751068,0.00009033558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884185,0.00001231086,0.0002023102,0.004151328,0.00005310717,0.0001468849,0.00005199373,0.0000119299,0.006951632],"genre_scores_gemma":[0.9986784,0.0002923506,0.0001232639,0.00001626797,0.00001588011,0.00001573108,0.00002828204,0.000006395756,0.0008234486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07628635,"threshold_uncertainty_score":0.39214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514472139848318,"score_gpt":0.285369145538383,"score_spread":0.2702244241398998,"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."}}