{"id":"W168001566","doi":"","title":"ROADIDEA INCO – A Comparison of North-American and European Data Availabilities and Applications","year":2011,"lang":"en","type":"article","venue":"elib (German Aerospace Center)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"European commission; European union; Work (physics); Scale (ratio); Commission; Computer science; Business; Data science; Engineering; International trade; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01442319,0.0004096914,0.0004121224,0.007639238,0.0009461116,0.005656737,0.001577418,0.0008041185,0.004082604],"category_scores_gemma":[0.01909575,0.000420474,0.000567844,0.018082,0.0009899659,0.004118497,0.003177009,0.00073138,0.001854765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003538671,"about_ca_system_score_gemma":0.005428225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06787455,"about_ca_topic_score_gemma":0.05448949,"domain_scores_codex":[0.9890832,0.002205804,0.0007958299,0.001704559,0.005170695,0.001039768],"domain_scores_gemma":[0.9752435,0.005702014,0.002292172,0.003514916,0.01187161,0.001375843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002983858,0.001063034,0.284012,0.002769724,0.0007582258,0.0009076739,0.01000773,0.01198647,0.009135596,0.08708309,0.1763931,0.4128995],"study_design_scores_gemma":[0.00007729483,0.0002447455,0.4922642,0.0004495775,0.0001818472,0.0005809022,0.009314573,0.007832739,0.005954233,0.002415909,0.4805415,0.0001424297],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6261777,0.006191877,0.02078495,0.005380617,0.0002748324,0.000403882,0.05970813,0.004219848,0.2768581],"genre_scores_gemma":[0.8763587,0.002733073,0.0186778,0.0007587586,0.0001075434,0.0004163165,0.08183299,0.001191505,0.01792341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06787455,"threshold_uncertainty_score":0.134959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812536116080342,"score_gpt":0.251449162191389,"score_spread":0.2233238010305856,"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."}}