{"id":"W2903512949","doi":"10.1109/apede.2018.8542363","title":"RFID Smart Shelf","year":2018,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"March of Dimes Canada","funders":"","keywords":"Computer science; Off the shelf; Internet of Things; Embedded system; Systems design; Systems engineering; Software engineering; Engineering","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":[0.0002519551,0.0004699993,0.000449397,0.0007089215,0.0005247041,0.001817974,0.001239329,0.001767323,0.02027824],"category_scores_gemma":[0.0004995429,0.0002859563,0.000448162,0.0008559867,0.0005133048,0.002131404,0.001061171,0.0006755215,0.02030223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003662886,"about_ca_system_score_gemma":0.0003400584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004246686,"about_ca_topic_score_gemma":0.0004237232,"domain_scores_codex":[0.9994556,0.00004416771,0.00003746117,0.00009455762,0.0003282887,0.00003997652],"domain_scores_gemma":[0.9996887,0.00003273384,0.00002747568,0.00008590103,0.0001412816,0.00002380232],"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":[0.0002235182,0.00009305458,0.001862509,0.001145369,0.00004355789,0.001347303,0.0004828587,0.003132976,0.1265868,0.2147952,0.04975617,0.6005307],"study_design_scores_gemma":[0.00002991614,0.0003292526,0.001070833,0.0001134467,0.00006466973,0.003520746,0.0001894309,0.007754331,0.0695954,0.01272147,0.9045524,0.00005803439],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02455951,0.01229403,0.6227622,0.001603758,0.003554366,0.0004309758,0.0007425426,0.005847021,0.3282056],"genre_scores_gemma":[0.2742744,0.01081929,0.2720068,0.003514581,0.0007577348,0.0003251853,0.001724131,0.0004229636,0.4361549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02027824,"threshold_uncertainty_score":0.06783748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006689572604297734,"score_gpt":0.1975650625064462,"score_spread":0.1908754899021485,"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."}}