{"id":"W4200329580","doi":"10.1145/3494994","title":"IMU2Doppler","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Activity recognition; Inertial measurement unit; Domain (mathematical analysis); Adaptation (eye); Context (archaeology); Domain adaptation; Artificial intelligence; Radar; Machine learning; Key (lock); Component (thermodynamics); Baseline (sea); Labeled data; Telecommunications","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":[0.00006587683,0.0001837283,0.0002308672,0.0001042442,0.00007684769,0.00004454201,0.0008056221,0.0001079529,0.000009677374],"category_scores_gemma":[0.0007918791,0.0001391375,0.00006622034,0.000293841,0.0001789826,0.0002642574,0.000910149,0.000426531,0.00000454111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006529225,"about_ca_system_score_gemma":0.000008650685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002837779,"about_ca_topic_score_gemma":9.503169e-7,"domain_scores_codex":[0.9992052,0.000002846436,0.000184186,0.0002450321,0.0001341568,0.0002286256],"domain_scores_gemma":[0.9991773,0.00009363693,0.00007625265,0.0004546933,0.0001824864,0.00001556931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000361704,0.0000799339,0.001679651,0.0002199297,0.00009833017,0.000004295979,0.000342174,0.0001740825,0.9102892,0.002304527,0.01207423,0.07269751],"study_design_scores_gemma":[0.00009064413,0.00008145178,0.0002104066,0.0002949153,0.00001224618,0.00003751994,0.00203868,0.0001801827,0.9480464,0.0425196,0.006339421,0.0001485417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850218,0.001789721,0.000073611,0.0008681747,0.0001993718,0.0003074089,0.00000935088,0.002357963,0.009372637],"genre_scores_gemma":[0.9921225,0.001056404,0.006346768,0.00003950452,0.00001705153,0.0001650083,3.13807e-7,0.00003329021,0.0002191454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07254896,"threshold_uncertainty_score":0.5673863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007790591688474904,"score_gpt":0.2391646379259003,"score_spread":0.2313740462374254,"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."}}