{"id":"W2338675176","doi":"10.3166/ts.32.147-167","title":"Construction précise de bases d’amers géo-référencés pour la localisation d’un véhicule en milieu urbain","year":2015,"lang":"fr","type":"article","venue":"Traitement du signal","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scale (ratio); Augmented reality; Global Positioning System; Computation; Service (business); Computer vision; Artificial intelligence; Computer graphics (images); Data mining; Cartography; Geography; Algorithm; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0009150243,0.0009286139,0.000733113,0.001769872,0.0007054788,0.001764387,0.001476088,0.001367469,0.004118532],"category_scores_gemma":[0.004005942,0.0007436805,0.0008869075,0.001412652,0.0007143156,0.001954588,0.002022459,0.001258176,0.00348106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008264781,"about_ca_system_score_gemma":0.001825225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01269915,"about_ca_topic_score_gemma":0.01364614,"domain_scores_codex":[0.9992108,0.0001143797,0.00003875471,0.0002052197,0.0003573943,0.00007343523],"domain_scores_gemma":[0.9988581,0.0002633016,0.00007798627,0.000250712,0.0005104828,0.00003941278],"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":[0.0002817166,0.00007597325,0.00335013,0.0003992695,0.00008004655,0.0004529862,0.0009919582,0.3918004,0.04805156,0.09145287,0.006231434,0.4568316],"study_design_scores_gemma":[0.00003634456,0.0001093947,0.002107182,0.0001428568,0.00004505644,0.000316568,0.0005216552,0.8656297,0.05738215,0.02423711,0.04940003,0.00007201757],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01076819,0.0001416085,0.985599,0.0000595026,0.00004687663,0.00002889944,0.0003502642,0.001011649,0.001993924],"genre_scores_gemma":[0.1974767,0.0004193615,0.7937859,0.00004751661,0.00002754865,0.0001601801,0.002173367,0.0003352596,0.005574129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01269915,"threshold_uncertainty_score":0.02525049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01387986546631736,"score_gpt":0.2122027496412381,"score_spread":0.1983228841749207,"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."}}