{"id":"W1974888697","doi":"10.3141/2178-08","title":"Freeway Sensor Spacing and Probe Vehicle Penetration","year":2010,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University; Portland State University","keywords":"Detector; Software deployment; Computer science; Simulation; Midpoint; Real-time computing; Travel time; Engineering; Transport engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002485113,0.0001761487,0.0002377182,0.0007416302,0.0003703382,0.0001495127,0.0004577788,0.0001713068,0.00009620865],"category_scores_gemma":[0.00007405383,0.0001412894,0.000141531,0.0009467492,0.0003552799,0.0006266793,0.000004917255,0.002295063,0.000009284048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007061232,"about_ca_system_score_gemma":0.0001051549,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0010684,"about_ca_topic_score_gemma":0.02537503,"domain_scores_codex":[0.9965488,0.0002565628,0.0007497689,0.0002330672,0.001690092,0.000521729],"domain_scores_gemma":[0.9979742,0.0002809047,0.0001247585,0.0003105435,0.001044135,0.000265458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008228887,0.0003907506,0.2796927,0.001245772,0.0004143173,0.0001857984,0.007131774,0.006043516,0.5419996,0.02306877,0.0611168,0.07788733],"study_design_scores_gemma":[0.001057479,0.0002949028,0.952193,0.000173422,0.00003913047,0.000001344969,0.00104006,0.004807068,0.01196157,0.001434479,0.02678155,0.000215943],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851959,0.00009102067,0.01103415,0.001368545,0.0006510243,0.0007390043,0.00002156641,0.000314727,0.000584078],"genre_scores_gemma":[0.9941089,0.0007819206,0.004608796,0.00001956369,0.0001829832,0.00004710993,0.000007553234,0.00004620446,0.0001969644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6725003,"threshold_uncertainty_score":0.9971033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03820064814406691,"score_gpt":0.3206293203928602,"score_spread":0.2824286722487933,"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."}}