{"id":"W4241108149","doi":"10.22215/etd/2009-09161","title":"EMC/EMI characterization using a novel 3D system on package","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; Library and Archives Canada","funders":"Indian National Science Academy","keywords":"EMI; Characterization (materials science); Computer science; Electromagnetic interference; Engineering; Materials science; Electronic engineering; Nanotechnology","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":[0.0002464142,0.0004415466,0.0004121166,0.0004303252,0.0003171334,0.0005936173,0.0006036754,0.0005414041,0.00418363],"category_scores_gemma":[0.0004530184,0.0002980403,0.0003127422,0.0003891019,0.0002688676,0.0005299784,0.0003577994,0.0003196504,0.0009248864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003579193,"about_ca_system_score_gemma":0.0004046363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00115943,"about_ca_topic_score_gemma":0.002479693,"domain_scores_codex":[0.9996552,0.00003909169,0.00001276113,0.0000598442,0.0001973869,0.00003577368],"domain_scores_gemma":[0.9995259,0.00007587836,0.00004918456,0.0001270567,0.0001977229,0.00002424307],"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":[0.0002088505,0.00006423954,0.002711867,0.0001467103,0.00003320838,0.0005333594,0.0006030683,0.005476472,0.9328935,0.002595172,0.005184127,0.04954937],"study_design_scores_gemma":[0.00003691679,0.0006923261,0.01615641,0.00002500894,0.0000819476,0.0009661081,0.0002497987,0.05578991,0.8838986,0.00044028,0.04154154,0.0001211228],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5398589,0.0003520624,0.4343636,0.0007828934,0.0005395163,0.0002201993,0.0008453362,0.005137215,0.01790022],"genre_scores_gemma":[0.8170357,0.0001874266,0.1619408,0.0002032945,0.00005118987,0.0001021207,0.0003480671,0.0004563153,0.01967499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00418363,"threshold_uncertainty_score":0.01399559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01045231403602739,"score_gpt":0.224421492343803,"score_spread":0.2139691783077756,"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."}}