{"id":"W4406285300","doi":"10.1016/j.martra.2025.100129","title":"Comparative and critical analysis of data sources used for ship traffic spatial pattern analysis in Canada and across the global Arctic","year":2025,"lang":"en","type":"article","venue":"Maritime Transport Research","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Transport Canada","funders":"Marine Environmental Observation Prediction and Response Network","keywords":"Arctic; Geography; Climatology; Environmental science; Oceanography; Meteorology; Physical geography; Geology","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":[0.002121231,0.00009821272,0.0005087973,0.0001869159,0.0007426012,0.00005126028,0.000439669,0.00005539701,0.0000540794],"category_scores_gemma":[0.000176358,0.00007433419,0.00007240925,0.002484941,0.001783913,0.00008532453,0.0001059287,0.0001906961,1.304128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001721341,"about_ca_system_score_gemma":0.0007575315,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9876248,"about_ca_topic_score_gemma":0.9997739,"domain_scores_codex":[0.9978745,0.0003807275,0.0002953717,0.0003757859,0.0005480839,0.0005255415],"domain_scores_gemma":[0.9972857,0.002175036,0.00002829497,0.0002683435,0.0001417966,0.0001007868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005687508,0.00003630622,0.9824736,0.00006463116,0.001321919,0.00000544053,0.01232855,0.00007484334,2.388242e-7,0.0007162116,0.00006468716,0.002856712],"study_design_scores_gemma":[0.0002209207,0.00001927396,0.9692135,0.0000170815,0.0007974007,7.036762e-8,0.02311491,0.005686145,0.000001427192,0.0003391395,0.0005168148,0.0000733529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816794,0.0004283871,0.00123804,0.01483944,0.00001497008,0.0003342933,0.001090619,0.000005220569,0.0003696801],"genre_scores_gemma":[0.999599,0.00007678813,0.00003263128,0.00006809609,0.00002278137,0.00002550657,0.00005892585,0.000002387473,0.0001138246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0179197,"threshold_uncertainty_score":0.65729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1149941681773939,"score_gpt":0.4595097495643669,"score_spread":0.344515581386973,"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."}}