{"id":"W4403886077","doi":"10.1007/978-981-97-8743-2_6","title":"SEBWatcher: Visual Analysis System for Subject, Environment and Behavior in Traffic Scenes","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Subject (documents); Computer science; Artificial intelligence; Information retrieval; Computer vision; World Wide Web","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":[0.0009517393,0.0001934287,0.0002952408,0.00188291,0.0003221857,0.0007167984,0.001432537,0.0001003336,0.000002419159],"category_scores_gemma":[0.000009635188,0.0001912645,0.00006320466,0.0007694465,0.0003982548,0.00271122,0.001793368,0.0001949184,0.00001550705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001768456,"about_ca_system_score_gemma":0.0001124364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009923879,"about_ca_topic_score_gemma":0.00002752074,"domain_scores_codex":[0.9984689,0.00002081587,0.0006714361,0.0003410224,0.0003129717,0.000184888],"domain_scores_gemma":[0.9984524,0.0001315317,0.0001928242,0.001034749,0.0001010285,0.00008742233],"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":[0.000002793062,0.00006228546,0.0003665768,0.0002344995,0.00004443489,0.000001485257,0.003717758,0.003241932,0.000002804841,0.8438189,0.00006156986,0.1484449],"study_design_scores_gemma":[0.0001835453,0.00003950273,0.0009949616,0.0001151461,0.00007355639,0.000007827853,0.00006561082,0.9712566,0.000003720616,0.0003173848,0.02671851,0.0002236649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001951458,0.001514959,0.9799173,0.0008661209,0.0003739256,0.00126364,0.0001366222,0.0002186293,0.01375736],"genre_scores_gemma":[0.8503677,0.008434176,0.1359282,0.0007800788,0.00007353078,0.0002834424,0.0007624493,0.00003456094,0.003335864],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9680147,"threshold_uncertainty_score":0.7799538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0350574373955958,"score_gpt":0.3160253471559575,"score_spread":0.2809679097603617,"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."}}