{"id":"W4292348639","doi":"10.1109/itc-egypt55520.2022.9855742","title":"Multi-Context Recommendation Systems (CARS) in Autonomous Driving and Other Applications","year":2022,"lang":"en","type":"article","venue":"2022 International Telecommunications Conference (ITC-Egypt)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recommender system; Computer science; Context (archaeology); Process (computing); Human–computer interaction; Data science; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00102989,0.000241477,0.0002910704,0.0005871002,0.0006349509,0.0004900999,0.002840428,0.00007874072,0.0003609606],"category_scores_gemma":[0.00005041546,0.0002799897,0.00007674477,0.0005822185,0.00006583648,0.000672726,0.001778363,0.0006245441,0.00002931557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005459667,"about_ca_system_score_gemma":0.0002038833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002351269,"about_ca_topic_score_gemma":0.001603478,"domain_scores_codex":[0.9974707,0.0005082785,0.0007866568,0.0006074455,0.0003257204,0.0003011932],"domain_scores_gemma":[0.9977338,0.0002846933,0.0004272352,0.001248063,0.0002117479,0.00009442342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007346326,0.0008957883,0.02962566,0.00002582943,0.0001493322,0.000003853966,0.00274267,0.0005378566,0.001097807,0.7150893,0.00295129,0.2468733],"study_design_scores_gemma":[0.0007224086,0.00006801207,0.006427523,0.00005126546,0.000008607405,0.0001045844,0.001385552,0.4433274,0.000107702,0.002835567,0.5445039,0.0004575307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008507838,0.001216487,0.9455778,0.01779523,0.001276563,0.002547476,0.0002129883,0.0008392457,0.02202634],"genre_scores_gemma":[0.9650454,0.0002277267,0.02941585,0.0005204565,0.00004635666,0.003562563,0.0001508574,0.00002795534,0.001002858],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9565375,"threshold_uncertainty_score":0.9999653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04870614933686333,"score_gpt":0.3003851794620342,"score_spread":0.2516790301251708,"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."}}