{"id":"W1993614505","doi":"10.1109/ths.2011.6107846","title":"Visual analytics for maritime domain awareness","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geoscience BC; Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Visualization; Computer science; Analytics; Domain (mathematical analysis); Mandate; Data science; Information overload; Task (project management); Data visualization; Anomaly detection; Human–computer interaction; World Wide Web; Data mining; Engineering; Systems engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001859964,0.00008307501,0.000105034,0.00008538069,0.00008262472,0.0001034656,0.0005543244,0.00003723588,0.0001567322],"category_scores_gemma":[0.00002429739,0.0000727697,0.00005395662,0.0002876316,0.0000252102,0.0003304487,0.0001545184,0.00002575746,0.00007283921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001178345,"about_ca_system_score_gemma":0.00005745704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000182654,"about_ca_topic_score_gemma":0.00002151992,"domain_scores_codex":[0.9992779,0.00001690579,0.0001675106,0.0002248081,0.0001272604,0.0001856534],"domain_scores_gemma":[0.9994424,0.0000335395,0.00004208782,0.0002974035,0.00009903895,0.00008554205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003136799,0.0001189047,0.001456143,0.0000140483,0.00001726191,0.000003491592,0.0001914521,0.000003840877,0.00003088481,0.9865599,0.007442867,0.004158079],"study_design_scores_gemma":[0.0005598809,0.0001906416,0.00159933,0.00001404302,0.00001935909,0.000007996565,0.0001418317,0.8820911,0.003930439,0.05030881,0.0607132,0.0004233812],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004598971,0.00000607134,0.9880524,0.0001213068,0.0001278238,0.00008010011,0.000008250722,0.0001432595,0.01100091],"genre_scores_gemma":[0.3181205,0.00001726237,0.6695377,0.003265609,0.0001284466,0.00002145085,0.00008867146,0.00002480656,0.008795594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9362511,"threshold_uncertainty_score":0.2967462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05793371599474906,"score_gpt":0.3273896484026644,"score_spread":0.2694559324079154,"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."}}