{"id":"W4391807625","doi":"10.1109/tvt.2024.3354751","title":"IEEE Vehicular Technology Society Information","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Digital Media and Visual Art","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Telecommunications; Engineering; Electrical engineering","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001761729,0.0003005625,0.0002767369,0.001181958,0.0002395595,0.0002680808,0.000994295,0.0006699981,0.00001872902],"category_scores_gemma":[0.00001086774,0.0002792711,0.0002777916,0.002948025,0.0002822368,0.001502782,0.00001395147,0.0008762236,0.001502351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001364128,"about_ca_system_score_gemma":0.0001300008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004859571,"about_ca_topic_score_gemma":0.000003377726,"domain_scores_codex":[0.9981464,0.00002197755,0.0004047312,0.0005320474,0.0003645091,0.0005303082],"domain_scores_gemma":[0.9988072,0.00005791207,0.00005767401,0.0008516303,0.0001306794,0.00009489943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009788503,0.0003387996,0.00001419168,0.0001627945,0.000341912,0.0001584742,0.0005641166,0.003937242,0.01702665,0.09520818,0.002814733,0.8794231],"study_design_scores_gemma":[0.0006785121,0.0009021613,0.00001025066,0.0002485485,0.0000799806,0.0005567803,0.00029064,0.2426787,0.4681647,0.02545343,0.260083,0.0008532509],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04722259,0.0002630615,0.9364902,0.009142278,0.002070518,0.0003188516,0.00001304826,0.004011728,0.000467773],"genre_scores_gemma":[0.9907815,0.0001221806,0.008028943,0.000557312,0.00003777603,0.0002124801,0.000003707605,0.00002391233,0.0002322176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9435589,"threshold_uncertainty_score":0.999966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008909428271126908,"score_gpt":0.2425454494135728,"score_spread":0.2336360211424459,"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."}}