{"id":"W7097893434","doi":"","title":"Canada Contents An interblock VLIW-targeted instruction scheduler for GCC 1","year":2006,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Documentation; Context (archaeology); Scheduling (production processes); Negotiation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001024829,0.0003377689,0.000214161,0.0006066218,0.00104413,0.0008554168,0.0007478498,0.000277891,0.05772207],"category_scores_gemma":[0.0004060887,0.0002426845,0.0001627046,0.0007780078,0.0001686933,0.0003337178,0.0003202042,0.0003585344,0.01204855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003254104,"about_ca_system_score_gemma":0.004993461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2751198,"about_ca_topic_score_gemma":0.4624535,"domain_scores_codex":[0.9998974,0.000007001031,0.00000413718,0.00001815735,0.00004992813,0.00002334714],"domain_scores_gemma":[0.9997706,0.00001125985,0.000005248608,0.0000161544,0.0001670906,0.00002964159],"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":[0.0007270278,0.0001214573,0.003607753,0.0003568208,0.00003406313,0.0004702804,0.0002221081,0.03245851,0.05493079,0.03937571,0.3445992,0.5230963],"study_design_scores_gemma":[0.0001303826,0.0001707254,0.004105287,0.0001410769,0.000074007,0.0001543757,0.000196076,0.1525881,0.06190988,0.01038515,0.7700806,0.000064261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.1070776,0.004794378,0.1966975,0.003103958,0.003892798,0.0005953612,0.009281388,0.06525239,0.6093047],"genre_scores_gemma":[0.3470291,0.002568851,0.1903139,0.0007528197,0.0002793086,0.0001032953,0.008530824,0.004013582,0.4464082],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2751198,"threshold_uncertainty_score":0.5470369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01366902557282765,"score_gpt":0.2327095315149561,"score_spread":0.2190405059421284,"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."}}