{"id":"W2153835435","doi":"10.1109/icwsi.1995.515455","title":"Yield improvement of a large area magnetic field sensor array design using redundancy schemes","year":2002,"lang":"en","type":"article","venue":"","topic":"Surface Roughness and Optical Measurements","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Redundancy (engineering); Very-large-scale integration; Yield (engineering); Magnetic field; Electronic engineering; Computer science; Laser; Engineering; Materials science; Reliability engineering; Physics; Optics","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":[0.0002486404,0.0004335901,0.0002543268,0.0002381534,0.0001291505,0.0002174953,0.0005781378,0.000254812,0.0006198392],"category_scores_gemma":[0.0007096674,0.0001597938,0.0001467458,0.0001454857,0.0001624302,0.0003295314,0.00016227,0.0001905837,0.0001885839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002885112,"about_ca_system_score_gemma":0.0002588017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003379453,"about_ca_topic_score_gemma":0.00048907,"domain_scores_codex":[0.999746,0.00003779893,0.0000144864,0.00005411504,0.0001168893,0.00003058016],"domain_scores_gemma":[0.9993464,0.0001536367,0.0001891268,0.0001002558,0.0001789914,0.00003151956],"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":[0.0001385776,0.00006169661,0.001216416,0.00006142983,0.00001748818,0.0001092849,0.00004581791,0.01029549,0.961329,0.0007626973,0.0001948053,0.0257673],"study_design_scores_gemma":[0.00004509761,0.002127175,0.004220511,0.000008832533,0.00004469181,0.0004786444,0.00003190905,0.1127149,0.8774643,0.0003281439,0.002510825,0.00002504393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8835337,0.0004197873,0.1131735,0.0001339201,0.00004040002,0.00005284974,0.00008470483,0.0007455895,0.001815619],"genre_scores_gemma":[0.9515572,0.00008842426,0.0472563,0.00002110975,0.00001679624,0.00002743946,0.00006740333,0.00001749453,0.0009478114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006198392,"threshold_uncertainty_score":0.002093315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06481582624853255,"score_gpt":0.2344543966096934,"score_spread":0.1696385703611608,"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."}}