{"id":"W4416876459","doi":"10.37665/smvziyr60439","title":"Survey of Successful RFID Case Studies in Electronics Manufacturing","year":2005,"lang":"","type":"article","venue":"SMTA International","topic":"RFID technology advancements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ABB (Canada)","funders":"","keywords":"Barcode; Electronics; Set (abstract data type); Control (management); Radio-frequency identification; Manufacturing; Tracking (education)","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":[0.009795838,0.0005907766,0.0004977704,0.008641653,0.00303367,0.003007563,0.002342783,0.002480867,0.004747132],"category_scores_gemma":[0.0365073,0.0007478726,0.0009117898,0.01214504,0.001974219,0.002960352,0.002618922,0.0007538595,0.001203323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002452532,"about_ca_system_score_gemma":0.001860464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002743969,"about_ca_topic_score_gemma":0.00437611,"domain_scores_codex":[0.9866906,0.006852011,0.001599617,0.0007898195,0.003115507,0.0009523872],"domain_scores_gemma":[0.9377695,0.04584715,0.005834252,0.003979873,0.00528289,0.001286294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006207153,0.003004755,0.2915111,0.00669285,0.0004018886,0.09407429,0.07455755,0.004833064,0.004913544,0.01974275,0.01984229,0.4798052],"study_design_scores_gemma":[0.00009333714,0.001598585,0.1697223,0.009176421,0.0004182478,0.1426281,0.2041171,0.005334414,0.02025573,0.00605659,0.4403628,0.0002364268],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9176157,0.03624953,0.01251855,0.002156935,0.0001212353,0.0008179741,0.0007238916,0.0001254832,0.02967072],"genre_scores_gemma":[0.9566639,0.02535358,0.01112703,0.0004739425,0.00003225431,0.0003292922,0.0008076733,0.00008543951,0.005126794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009795838,"threshold_uncertainty_score":0.05180597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02905240966523186,"score_gpt":0.3239894278037403,"score_spread":0.2949370181385084,"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."}}