{"id":"W2576948029","doi":"","title":"Hotspots for Vessel-to-Vessel and Vessel-to-Fix Object Accidents Along the Great Lakes Seaway","year":2016,"lang":"en","type":"article","venue":"UWSpace (University of Waterloo)","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Object (grammar); Research vessel; Geology; Forensic engineering; Marine engineering; Engineering; Oceanography; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001996491,0.0001757687,0.0002370993,0.0001433725,0.0002078316,0.00003139114,0.0003303531,0.00009761059,0.0001686604],"category_scores_gemma":[0.00002824903,0.0001387408,0.00007861642,0.0002124556,0.00006760211,0.0002785369,0.0001159189,0.00007923525,0.0000858082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005470352,"about_ca_system_score_gemma":0.00001725291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001754629,"about_ca_topic_score_gemma":0.002444989,"domain_scores_codex":[0.9991173,0.00003473669,0.0001058498,0.0002495153,0.0001806363,0.0003119566],"domain_scores_gemma":[0.9992429,0.0001371517,0.00003634076,0.0002983085,0.00009697558,0.0001883008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00129562,0.0002117418,0.07548996,0.001464713,0.001135122,0.0001216704,0.199473,0.004591076,0.3101627,0.003081933,0.2520378,0.1509346],"study_design_scores_gemma":[0.0103536,0.0007535104,0.7005885,0.001387416,0.0004865968,0.00005153051,0.04585495,0.006035688,0.05159,0.001058804,0.17932,0.002519404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908015,0.00004194775,0.001800834,0.006172676,0.000177119,0.0004678,0.0000782253,0.0001385663,0.0003213208],"genre_scores_gemma":[0.9466877,0.0001012864,0.001191168,0.0001024922,0.00005067039,0.000002621986,0.000009997681,0.00002996237,0.05182412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6250985,"threshold_uncertainty_score":0.5657685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009134714257550407,"score_gpt":0.1953264970496063,"score_spread":0.1861917827920559,"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."}}