{"id":"W4416726322","doi":"10.23919/oceans59106.2025.11245174","title":"Navigating the Annotation Bottleneck: Active Learning for Scalable Maritime Data Analytics","year":2025,"lang":"","type":"article","venue":"","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Larus Technologies (Canada); University of Ottawa","funders":"","keywords":"Scalability; Bottleneck; Pipeline (software); Active learning (machine learning); Annotation; Identification (biology); Analytics; Mobile device; Macro","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002857076,0.001108467,0.001315512,0.001220621,0.0008239257,0.001884015,0.004165791,0.001434147,0.001382416],"category_scores_gemma":[0.008030578,0.0006851194,0.0008882648,0.001855097,0.001054052,0.004483487,0.002579178,0.002251537,0.0006583974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231041,"about_ca_system_score_gemma":0.001610824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007895943,"about_ca_topic_score_gemma":0.008306943,"domain_scores_codex":[0.9986498,0.0003454855,0.00008123207,0.0003911939,0.0004219656,0.0001104244],"domain_scores_gemma":[0.9959089,0.002531604,0.000232619,0.000601469,0.0006150681,0.0001104519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003829605,0.0003738693,0.002414501,0.0001694551,0.0001307352,0.0001390366,0.0003220339,0.433088,0.0112078,0.009351847,0.006073929,0.5363458],"study_design_scores_gemma":[0.00000946358,0.00001912401,0.00008461739,0.000003118639,0.000005978266,0.000008478471,0.00002200932,0.9928901,0.001911475,0.004582714,0.0004587875,0.000004115245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02309432,0.0002993377,0.9723664,0.0002962871,0.00004137718,0.00005906406,0.0001622922,0.003049627,0.0006313261],"genre_scores_gemma":[0.4986072,0.0003021384,0.4968313,0.0003051148,0.000113183,0.0002910032,0.001306267,0.0003475583,0.001896211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007895943,"threshold_uncertainty_score":0.01569998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806974671349698,"score_gpt":0.31007494488969,"score_spread":0.282005198176193,"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."}}