{"id":"W2151071289","doi":"10.1109/icwsi.1993.255261","title":"Fault tolerance in a wafer scale environment","year":2002,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Australian Government; CMC Microsystems","keywords":"Computer science; Nondeterministic algorithm; USable; Set (abstract data type); Network packet; Fault tolerance; Routing (electronic design automation); Wafer-scale integration; Scale (ratio); Backplane; Distributed computing; Parallel computing; Very-large-scale integration; Algorithm; Embedded system; Computer network; Computer hardware","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":[0.0001169011,0.0002389558,0.0003269216,0.0002197804,0.0002832621,0.0006224233,0.00045783,0.000644079,0.002918971],"category_scores_gemma":[0.0005964237,0.0001194997,0.0001997177,0.0002978088,0.0003948825,0.000587552,0.0006575001,0.0003377437,0.001023429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002761168,"about_ca_system_score_gemma":0.0002274717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002849958,"about_ca_topic_score_gemma":0.0003271982,"domain_scores_codex":[0.9998355,0.00002767101,0.000005666835,0.00003142517,0.00006535991,0.00003440167],"domain_scores_gemma":[0.999795,0.0000735489,0.00003172937,0.00005775513,0.00002973856,0.00001217787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002177473,0.0000708661,0.001855009,0.0003540069,0.00005501957,0.001289751,0.0001682442,0.4697841,0.1842748,0.07332237,0.01241569,0.2561924],"study_design_scores_gemma":[0.00007446259,0.0004839123,0.00220302,0.00004723125,0.0000453362,0.001138223,0.0001594041,0.7598877,0.08726272,0.07848071,0.07015823,0.00005905933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2080405,0.003020876,0.7386732,0.001439522,0.0003824436,0.00005588478,0.0003124714,0.005545726,0.04252932],"genre_scores_gemma":[0.9070862,0.001515549,0.07952543,0.0002962136,0.0001016049,0.00008408005,0.0002935429,0.0002191537,0.01087822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002918971,"threshold_uncertainty_score":0.00976491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440772393814357,"score_gpt":0.1918296860628057,"score_spread":0.1774219621246621,"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."}}