{"id":"W2950841231","doi":"10.1145/2692916.2555267","title":"A general technique for non-blocking trees","year":2014,"lang":"en","type":"preprint","venue":"ACM SIGPLAN Notices","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Blocking (statistics); Computer science; Tree (set theory); Java; Word (group theory); Class (philosophy); Theoretical computer science; Algorithm; Parallel computing; Programming language; Mathematics; Combinatorics; Artificial intelligence; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006281586,0.0003991365,0.0005935479,0.0001352968,0.0001689241,0.0006048363,0.00402356,0.0004053175,0.00000406248],"category_scores_gemma":[0.0002048099,0.0003615936,0.0002261725,0.0001378296,0.0000405205,0.0001965666,0.001648234,0.0003902018,0.00002300429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005038332,"about_ca_system_score_gemma":0.0001285666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002149966,"about_ca_topic_score_gemma":0.00007255239,"domain_scores_codex":[0.9976813,0.00007191463,0.0004979108,0.0009384685,0.0003202796,0.0004900805],"domain_scores_gemma":[0.9967716,0.0003530318,0.000483473,0.002104493,0.0001646193,0.0001227912],"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":[0.0003262842,0.001447403,0.01323805,0.01458526,0.002077992,0.0004356213,0.01097224,0.1327149,0.07630387,0.154684,0.3032193,0.2899951],"study_design_scores_gemma":[0.001449287,0.0004079918,0.003866059,0.002415538,0.0001353277,0.00004931909,0.00005287219,0.784125,0.0225911,0.0284974,0.1535871,0.002822974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01111798,0.0002250985,0.9830559,0.0008179825,0.001779096,0.001237873,0.0001799934,0.0003008231,0.001285217],"genre_scores_gemma":[0.818832,0.000008118041,0.1788086,0.000259777,0.0008902565,0.0007178989,0.0001190159,0.00002940465,0.0003349153],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.807714,"threshold_uncertainty_score":0.9998836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02462820683101105,"score_gpt":0.2829371405244755,"score_spread":0.2583089336934645,"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."}}