{"id":"W2040401447","doi":"10.1109/tim.2014.2321461","title":"Low-Contact Resistance Probe Card Using MEMS Technology","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"3D IC and TSV technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Microelectromechanical systems; Wafer; Contact resistance; Wafer testing; Return loss; Materials science; Die (integrated circuit); Integrated circuit; Electrical engineering; Insertion loss; Electronic circuit; Electronic engineering; Optoelectronics; Engineering; Nanotechnology; Layer (electronics)","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":[0.0005317904,0.0004568662,0.0005299092,0.0005616511,0.0002387533,0.0005891515,0.001183059,0.0008856775,0.005830224],"category_scores_gemma":[0.001340127,0.0002821193,0.0002195528,0.000407395,0.00030885,0.001229293,0.0006728086,0.0006136835,0.002050051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000306846,"about_ca_system_score_gemma":0.0003158841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002448864,"about_ca_topic_score_gemma":0.0004964794,"domain_scores_codex":[0.9989065,0.0001650522,0.00006383903,0.0002499471,0.0005333817,0.0000813796],"domain_scores_gemma":[0.9987423,0.0004133807,0.0002386692,0.0003026656,0.000257205,0.00004579216],"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":[0.0002711793,0.0001231389,0.003444104,0.0001881249,0.00003298159,0.0001822502,0.00007901573,0.000673915,0.8798248,0.002851201,0.003881809,0.1084475],"study_design_scores_gemma":[0.000091877,0.001680497,0.01148993,0.00001744826,0.00004674109,0.001695695,0.00005113384,0.02402559,0.930498,0.0005022729,0.02982233,0.00007857315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3759611,0.001066197,0.5937361,0.000610815,0.0005576817,0.0008343061,0.001281144,0.01084636,0.01510626],"genre_scores_gemma":[0.71997,0.0002599657,0.268212,0.0003635887,0.0001255911,0.000406502,0.0006675873,0.000144281,0.009850568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005830224,"threshold_uncertainty_score":0.01950407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384830864490771,"score_gpt":0.2209793983538635,"score_spread":0.1971310897089557,"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."}}