{"id":"W4321780031","doi":"10.1109/ojsp.2023.3249121","title":"Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO","year":2023,"lang":"en","type":"article","venue":"IEEE Open Journal of Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); Western University","funders":"","keywords":"Rigid body; Compressed sensing; Computer science; Specular reflection; Reflection (computer programming); Computer vision; SIGNAL (programming language); Algorithm; Physics; Optics","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":[0.0002482202,0.0006596209,0.0004799931,0.0002239308,0.0002185246,0.0004322098,0.0004907404,0.0004608923,0.00053554],"category_scores_gemma":[0.0007756511,0.0002041432,0.0003564208,0.0003394304,0.0003425357,0.0005986579,0.0008490292,0.0004583352,0.000253769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001674012,"about_ca_system_score_gemma":0.0003075589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001489375,"about_ca_topic_score_gemma":0.001532636,"domain_scores_codex":[0.9996209,0.00009013079,0.00001552912,0.00008358296,0.0001354079,0.00005442878],"domain_scores_gemma":[0.9997846,0.00005652366,0.00005355238,0.00004412398,0.0000472135,0.00001395227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005042597,0.0001070668,0.004405767,0.0003292314,0.0001385391,0.0007119012,0.0003927785,0.4703803,0.1597709,0.02186073,0.00291764,0.3384809],"study_design_scores_gemma":[0.00001714433,0.0001802476,0.001358625,0.00001238592,0.00002214545,0.000187333,0.00004961028,0.9818296,0.01244414,0.002509436,0.001367558,0.00002169395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05468581,0.0003975105,0.9411973,0.0001976914,0.00007714643,0.00002344818,0.00006363042,0.0002872566,0.003070201],"genre_scores_gemma":[0.8981657,0.0005045217,0.09850482,0.000156042,0.00007785795,0.00006541769,0.0001311475,0.00001408843,0.002380522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001489375,"threshold_uncertainty_score":0.002961457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328825873829421,"score_gpt":0.222666909625973,"score_spread":0.1993786508876788,"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."}}