{"id":"W1511485029","doi":"10.1109/vnis.1989.98788","title":"Road information systems; impact of geographic information systems technology to automatic vehicle navigation and guidance","year":2003,"lang":"en","type":"article","venue":"","topic":"Web Applications and Data Management","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Information system; Service (business); Geographic information system; Fleet management; Intelligent transportation system; Transport engineering; Systems engineering; Telecommunications; Engineering; Remote sensing; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0004563598,0.00009911748,0.00014186,0.0005240385,0.00008166549,0.0003119177,0.0003304412,0.00005855341,0.000001563767],"category_scores_gemma":[0.00004054519,0.00008332169,0.00002402684,0.0008694716,0.00002278163,0.003214832,0.0001149765,0.00004374245,0.00007311526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005697755,"about_ca_system_score_gemma":0.00003667383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005926869,"about_ca_topic_score_gemma":0.000001556036,"domain_scores_codex":[0.9989939,0.00003098026,0.0005001293,0.00011265,0.0002076557,0.0001546686],"domain_scores_gemma":[0.9988999,0.00001383498,0.0002427916,0.0005868947,0.0001981459,0.00005844434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000171746,0.00002943446,0.01003306,0.000326165,0.000035565,1.522364e-7,0.0003462475,0.009868065,0.0002327087,0.9322245,0.0008380295,0.04606438],"study_design_scores_gemma":[0.0004651806,0.0002062571,0.06822545,0.00014239,0.00001164496,0.00002685482,0.0004368855,0.9139155,0.0002336167,0.0005841217,0.0155002,0.000251867],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2415159,0.00009199076,0.7544235,0.000114022,0.00009235441,0.0008573327,0.00001129275,0.0002174034,0.002676231],"genre_scores_gemma":[0.9881824,0.000006996338,0.01159295,0.00003313832,0.000003049753,0.0001460638,0.00002080091,0.000001978108,0.00001262923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9316403,"threshold_uncertainty_score":0.339776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005326871832337605,"score_gpt":0.241563831927421,"score_spread":0.2362369600950834,"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."}}