{"id":"W2887357719","doi":"10.5555/3199700.3199819","title":"DATC RDF: robust design flow database","year":2017,"lang":"en","type":"article","venue":"International Conference on Computer Aided Design","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Microsemi (Canada)","funders":"","keywords":"Computer science; RDF; Database; Design flow; Physical design; Database design; Data mining; Information retrieval; Circuit design; Semantic Web; Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004182154,0.0003128698,0.0002484526,0.0001887213,0.0002102115,0.0007166558,0.001571922,0.0001195261,0.0004224055],"category_scores_gemma":[0.00005580434,0.0003109517,0.00007559791,0.00004006083,0.00007994094,0.0006657638,0.0001635217,0.0003110992,0.0003398055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009485697,"about_ca_system_score_gemma":0.0000596212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001735095,"about_ca_topic_score_gemma":0.000002068932,"domain_scores_codex":[0.998476,0.00008882386,0.0003175164,0.0004073885,0.0004033604,0.0003069685],"domain_scores_gemma":[0.9985201,0.0001567335,0.0001026241,0.0008940619,0.0001949546,0.000131462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002565352,0.0002589135,0.0001208581,0.00006179671,0.0005030969,0.0004987264,0.0003635332,0.3291876,0.01772181,0.03603176,0.2413175,0.3736779],"study_design_scores_gemma":[0.0004320769,0.0001371092,0.0001775402,0.0001698385,0.00001115145,0.00002214917,0.000003831475,0.9797432,0.01377437,0.003764894,0.001395109,0.0003687705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001459878,0.00001870839,0.9878664,0.0003164856,0.001494853,0.0003279565,0.00005298619,0.0006818536,0.009094778],"genre_scores_gemma":[0.5623229,0.0001113321,0.4364297,0.0002275153,0.0004990377,0.0000632775,0.00005430109,0.00004775285,0.0002441613],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6505556,"threshold_uncertainty_score":0.9999343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1613731612330931,"score_gpt":0.2988426916609667,"score_spread":0.1374695304278735,"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."}}