{"id":"W4300957756","doi":"10.48550/arxiv.1703.10731","title":"An analysis of budgeted parallel search on conditional Galton-Watson\\n trees","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada","keywords":"Limit (mathematics); Overhead (engineering); Simple (philosophy); Set (abstract data type); Computer science; Tree (set theory); Process (computing); Mathematics; Combinatorics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.003403977,0.0006142055,0.001009047,0.001205777,0.0009025881,0.001427103,0.001876359,0.0008940243,0.004957882],"category_scores_gemma":[0.02377364,0.0005967069,0.0005632417,0.001696236,0.002035159,0.003755828,0.001978831,0.001382007,0.000436208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002239665,"about_ca_system_score_gemma":0.001710828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003938352,"about_ca_topic_score_gemma":0.003400941,"domain_scores_codex":[0.9983267,0.0006328148,0.00007674492,0.0001957682,0.0004585951,0.0003093584],"domain_scores_gemma":[0.9884723,0.008724131,0.0006929674,0.0009936028,0.0006810464,0.0004358736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007377819,0.0001412574,0.003903696,0.0002255565,0.00007508149,0.000170262,0.0003444459,0.7312113,0.006529349,0.2060952,0.003994947,0.04657114],"study_design_scores_gemma":[0.00002419372,0.0000306071,0.0002533465,0.00001328144,0.00001046668,0.00003030625,0.00001892229,0.9584458,0.0008552441,0.0398074,0.0005044807,0.000005883729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4834331,0.00275818,0.4948416,0.001902714,0.00008550144,0.0001589458,0.0003087888,0.001037834,0.0154732],"genre_scores_gemma":[0.9055979,0.0009331366,0.08831279,0.0002062263,0.00009103785,0.0002281101,0.0003247029,0.0003206409,0.00398555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004957882,"threshold_uncertainty_score":0.01800215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09572846714589092,"score_gpt":0.2439817270328835,"score_spread":0.1482532598869926,"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."}}