{"id":"W4385585286","doi":"10.1145/3587135.3592204","title":"T-RecX","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Classifier (UML); Spotting; Benchmark (surveying); Artificial intelligence; Deep learning; Keyword spotting; Enhanced Data Rates for GSM Evolution; Internet of Things; Edge device; Suite; Machine learning; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006991986,0.001860352,0.000593756,0.000734971,0.0004607543,0.001242563,0.003564114,0.001073164,0.01836176],"category_scores_gemma":[0.002598245,0.000603869,0.0009089828,0.0006802756,0.0004552768,0.00316773,0.001748096,0.001497761,0.007332271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128011,"about_ca_system_score_gemma":0.001338956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01098153,"about_ca_topic_score_gemma":0.01523077,"domain_scores_codex":[0.9995208,0.0000512025,0.00003269246,0.0001635743,0.0001463047,0.00008552883],"domain_scores_gemma":[0.9993135,0.0001389035,0.00005355793,0.0003057834,0.0001512192,0.00003709525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001260847,0.0005045326,0.003750392,0.0009121114,0.0002973424,0.0005411368,0.0001622389,0.08792906,0.02036949,0.01077798,0.2793262,0.5941688],"study_design_scores_gemma":[0.0003607151,0.001059502,0.002128888,0.0001031675,0.0001230712,0.0005448593,0.0001660881,0.8308585,0.04838656,0.01212502,0.1040758,0.00006777648],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.2234673,0.004450157,0.2850276,0.002276432,0.002034789,0.001266589,0.01667992,0.3795992,0.08519803],"genre_scores_gemma":[0.530869,0.001711205,0.3286611,0.002028283,0.0002445925,0.001426734,0.05298561,0.01005262,0.07202083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01836176,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03007279720246612,"score_gpt":0.2905801722133016,"score_spread":0.2605073750108354,"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."}}