{"id":"W3002224656","doi":"10.1109/jiot.2020.2967788","title":"Blockchain-Enabled Cross-Domain Object Detection for Autonomous Driving: A Model Sharing Approach","year":2020,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"China Postdoctoral Science Foundation; Mitacs; National Natural Science Foundation of China","keywords":"Computer science; Reliability (semiconductor); Domain (mathematical analysis); Distributed computing; Object (grammar); Blockchain; Adaptation (eye); Task (project management); Object detection; Data modeling; Resource (disambiguation); Artificial intelligence; Data mining; Real-time computing; Computer network; Computer security; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001654241,0.0006344958,0.001139106,0.0005783395,0.0008486442,0.001071953,0.002124537,0.001110048,0.002081086],"category_scores_gemma":[0.003271948,0.0004402341,0.0006299639,0.0007558204,0.001004445,0.003380189,0.003036823,0.001364583,0.0005078137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008631792,"about_ca_system_score_gemma":0.001850217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006566278,"about_ca_topic_score_gemma":0.005759667,"domain_scores_codex":[0.9991441,0.0001934688,0.00004532418,0.0002436396,0.0002339462,0.0001394337],"domain_scores_gemma":[0.9984533,0.0005010663,0.0001649789,0.0004392274,0.0003244566,0.0001169884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002356868,0.000163432,0.002538787,0.00006449338,0.00008311772,0.0002661541,0.0001950412,0.8256928,0.008486347,0.01626247,0.001829124,0.1441825],"study_design_scores_gemma":[0.000004213778,0.00001196058,0.00005918854,0.000001244381,0.000002769069,0.00001551784,0.000009234835,0.9947265,0.0008017134,0.004125659,0.0002386472,0.000003423367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04854605,0.0001865135,0.9480364,0.0003120315,0.00003836957,0.0000629739,0.0000693725,0.0007644543,0.001983784],"genre_scores_gemma":[0.9203258,0.0001275746,0.07620867,0.0001389062,0.00002590585,0.00008620087,0.0001992006,0.00007455455,0.002813307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006566278,"threshold_uncertainty_score":0.01305616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02231498841237644,"score_gpt":0.2578741325411596,"score_spread":0.2355591441287831,"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."}}