{"id":"W2115853254","doi":"","title":"U.S. and Canada Maneuvers","year":2008,"lang":"en","type":"article","venue":"Offline data","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Geography; Environmental science; Meteorology; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002173492,0.00003954468,0.00003812736,0.00001591586,0.00002265097,0.000003642235,0.0001380333,0.00001115298,0.00001280775],"category_scores_gemma":[0.000004528643,0.00004043658,0.000002305339,0.00002289532,0.00001120951,0.00007962363,0.00007593088,0.00003718002,0.000002737772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001201832,"about_ca_system_score_gemma":0.00001221163,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04439485,"about_ca_topic_score_gemma":0.1999596,"domain_scores_codex":[0.99976,0.000001657493,0.00004821464,0.00007553895,0.00005354068,0.0000610674],"domain_scores_gemma":[0.9996913,0.000004010673,0.000003737803,0.0002689549,0.000002991364,0.00002899398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[3.979834e-7,0.000001565861,0.0001724011,0.000007902448,0.000006466175,0.00001653883,0.000003845002,0.00008285607,0.00001539599,0.00005333672,0.9949812,0.004658153],"study_design_scores_gemma":[0.0000773945,0.000002624542,0.001907641,0.000002702413,0.000003957813,0.00001392126,0.000008103893,0.05351064,0.00006703151,0.000001483673,0.9443503,0.00005421844],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4636625,0.003804567,0.2179619,0.005566912,0.005169524,0.001417987,0.007118735,0.04030231,0.2549956],"genre_scores_gemma":[0.9973676,0.000806859,0.001085185,0.0001402156,0.00003335461,0.000001480976,0.0003691198,0.000006997978,0.0001891635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5337051,"threshold_uncertainty_score":0.9619686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216363652481666,"score_gpt":0.1837126713289405,"score_spread":0.1620763060807739,"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."}}