{"id":"W1555804989","doi":"","title":"Radar and radio data fusion platform for future intelligent transportation system","year":2010,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Radar; Chirp; Ambiguity function; Computer science; Electronic engineering; Frequency modulation; Digital radio frequency memory; Frequency-shift keying; Software-defined radio; Continuous-wave radar; Real-time computing; Waveform; Engineering; Radio frequency; Telecommunications; Demodulation; Radar imaging; Channel (broadcasting); Physics; Laser","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005584331,0.0002792884,0.000245648,0.0002951737,0.0002278746,0.0006922223,0.0005783328,0.0005933792,0.001991905],"category_scores_gemma":[0.0004285349,0.0001062631,0.0002159206,0.0001774424,0.0002307306,0.0008706872,0.0004741464,0.0004797655,0.0005573762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003862432,"about_ca_system_score_gemma":0.0005766422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000555346,"about_ca_topic_score_gemma":0.0006188526,"domain_scores_codex":[0.999702,0.00006898208,0.00001642943,0.00005126783,0.0001251545,0.00003607975],"domain_scores_gemma":[0.9998128,0.00002845373,0.00002951311,0.00002569862,0.00008497252,0.00001856525],"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":[0.0006326085,0.0002383723,0.002672798,0.000349202,0.0001225841,0.0004944193,0.0002567008,0.06791826,0.2942517,0.08315456,0.009304787,0.5406039],"study_design_scores_gemma":[0.0001641711,0.00178946,0.002654712,0.00009420302,0.0001671861,0.0007788697,0.0001436946,0.6686567,0.1857927,0.01865997,0.1209929,0.000105423],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03605442,0.001085641,0.9527391,0.0005975778,0.0002321595,0.00008580201,0.00006308545,0.001367368,0.007774928],"genre_scores_gemma":[0.6656708,0.0007009858,0.3227794,0.0004822461,0.0002502308,0.0001464893,0.0002881356,0.0000521537,0.009629643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001991905,"threshold_uncertainty_score":0.006663561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009370400512618171,"score_gpt":0.2092326409514045,"score_spread":0.1998622404387863,"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."}}