{"id":"W2336236367","doi":"10.1145/2899381","title":"Eh?Placer","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Design Automation of Electronic Systems","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Calgary","funders":"Chinese University of Hong Kong; University of Hong Kong; Alberta Innovates - Technology Futures","keywords":"Placer mining; Computer science; Variety (cybernetics); Process (computing); Physical design; Focus (optics); Margin (machine learning); Industrial engineering; Geology; Artificial intelligence; Programming language; Integrated circuit; Machine learning","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008404392,0.001197911,0.001058739,0.0008332974,0.0007650495,0.001705938,0.002458283,0.001260732,0.02995732],"category_scores_gemma":[0.00270491,0.0004958393,0.001269415,0.0009408299,0.0006574413,0.002093379,0.003003706,0.001162574,0.01039089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006608992,"about_ca_system_score_gemma":0.001154509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174091,"about_ca_topic_score_gemma":0.003072126,"domain_scores_codex":[0.9989821,0.0001493256,0.00006996962,0.000228514,0.0004091671,0.0001607518],"domain_scores_gemma":[0.9989291,0.0003296703,0.00007839823,0.0003952378,0.0002245345,0.00004305617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004023529,0.0001186245,0.001046367,0.0009879811,0.00008346779,0.0003896613,0.0001705886,0.1262206,0.0111141,0.08982289,0.06451672,0.7051266],"study_design_scores_gemma":[0.0002005501,0.000390896,0.0007532568,0.0001887205,0.00008021058,0.001175981,0.0002727763,0.6324929,0.03878202,0.1358591,0.1897023,0.0001013056],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.007686137,0.0006671055,0.9506609,0.0004119609,0.0002786475,0.0001834615,0.0008316903,0.01628281,0.02299725],"genre_scores_gemma":[0.169326,0.0008834017,0.7987484,0.0005502161,0.0001618089,0.00018714,0.002816455,0.002994806,0.02433182],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9700427,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515586658912994,"score_gpt":0.2190371016718792,"score_spread":0.2038812350827493,"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."}}