{"id":"W2042388146","doi":"10.1109/ecai.2013.6636212","title":"More evidence that SRHD-SGI produces hard SAT instances","year":2013,"lang":"en","type":"article","venue":"","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Encoding (memory); Computer science; Solver; Algorithm; Scheme (mathematics); Theoretical computer science; Parallel computing; Mathematics; Artificial intelligence; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003216517,0.0001618818,0.0001830475,0.00005784116,0.0001366435,0.0006480859,0.001145029,0.00005819123,0.0001061149],"category_scores_gemma":[0.00008501692,0.0001052656,0.00006192142,0.0002859714,0.00008157321,0.001943154,0.0002360837,0.00009404639,0.00128537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002688355,"about_ca_system_score_gemma":0.00005531239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005668016,"about_ca_topic_score_gemma":0.00006428297,"domain_scores_codex":[0.9984396,0.00005933134,0.0001955844,0.0005358098,0.0004108567,0.0003588849],"domain_scores_gemma":[0.9988375,0.00007735692,0.0001311406,0.0007156179,0.0001289265,0.0001094217],"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":[0.000005349548,0.0001414586,0.1121838,0.000204818,0.00005994045,0.00002891448,0.006415934,0.00001384418,0.00216828,0.3841366,0.04322338,0.4514177],"study_design_scores_gemma":[0.00128335,0.001197847,0.2602319,0.0002820093,0.00004419773,0.0002354475,0.004159685,0.01660844,0.06950303,0.144966,0.4979962,0.003492004],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2127759,0.009099894,0.6978921,0.01773021,0.004769139,0.002572748,5.198023e-7,0.002264546,0.05289494],"genre_scores_gemma":[0.9825952,0.00005818696,0.009292954,0.0005010778,0.00015302,0.00008515495,5.968932e-7,0.000006778911,0.007307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7698193,"threshold_uncertainty_score":0.9994922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0695353267414304,"score_gpt":0.2721627018800113,"score_spread":0.2026273751385809,"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."}}