{"id":"W7160158898","doi":"10.1109/iccv51701.2025.00793","title":"Beyond Pixel Uncertainty: Bounding the OoD Objects in Road Scenes","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Pixel; Object (grammar); Bounding overwatch; Feature (linguistics); Object detection","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001063001,0.0002801975,0.0003123193,0.0004205898,0.0005165816,0.00170398,0.001875451,0.0001142656,0.0001912477],"category_scores_gemma":[0.0003119328,0.0002046624,0.0001086627,0.003415117,0.0002057042,0.0006563645,0.001018974,0.0002712187,0.0001141626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001456682,"about_ca_system_score_gemma":0.0007248131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004398436,"about_ca_topic_score_gemma":0.001921201,"domain_scores_codex":[0.9974211,0.0002479508,0.00063732,0.0006748924,0.0004398504,0.0005788783],"domain_scores_gemma":[0.9983644,0.0002142466,0.000137001,0.001034171,0.0001501404,0.0001000701],"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":[0.000007971238,0.000233372,0.002808705,0.00007501042,0.00005654018,0.00001072531,0.002504627,0.001549899,0.0001209572,0.8927841,0.006934742,0.09291334],"study_design_scores_gemma":[0.0006659354,0.00004287919,0.001952231,0.0002940965,0.00003196481,0.000003070945,0.001671225,0.954614,0.0003430103,0.01563504,0.02443513,0.0003114165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009841905,0.002315555,0.7747926,0.0218628,0.004924577,0.000760957,0.00002028711,0.0002113067,0.1852701],"genre_scores_gemma":[0.9666258,0.0004681659,0.001024702,0.009264613,0.0001018917,0.000008943164,0.00001350142,0.00001041701,0.02248194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.956784,"threshold_uncertainty_score":0.9993324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01985589265385124,"score_gpt":0.316670535067669,"score_spread":0.2968146424138177,"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."}}