{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003988787,0.00276208,0.001712452,0.00730057,0.0009630807,0.004796059,0.004846143,0.002259675,0.03046476],"category_scores_gemma":[0.01354049,0.001488893,0.002391211,0.004689626,0.0009191083,0.00511419,0.002586019,0.002417913,0.01580388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003007031,"about_ca_system_score_gemma":0.004357586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366279,"about_ca_topic_score_gemma":0.009976239,"domain_scores_codex":[0.9959024,0.0006230574,0.000782812,0.0008108233,0.001625434,0.0002555056],"domain_scores_gemma":[0.9909344,0.002280253,0.0006307462,0.004098244,0.00187138,0.0001849484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001470896,0.0004158219,0.004990377,0.003833136,0.0003702517,0.0007685957,0.0004028834,0.09581129,0.01038541,0.1096664,0.5482092,0.2236758],"study_design_scores_gemma":[0.0003293935,0.0001205066,0.001014088,0.0005396276,0.0001929433,0.0004934656,0.0001043413,0.1010051,0.02566799,0.0413749,0.8289483,0.0002094427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004173984,0.001057298,0.487166,0.0007852912,0.0003584165,0.0008678837,0.3000692,0.1810804,0.02444152],"genre_scores_gemma":[0.06078498,0.001644959,0.2232224,0.001328851,0.0001735465,0.002054252,0.6787282,0.02033171,0.01173109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03046476,"threshold_uncertainty_score":0.1019148,"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."}}