{"id":"W2265246327","doi":"","title":"On the empirical time complexity of random 3-SAT at the phase transition","year":2015,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Satisfiability; DPLL algorithm; Scaling; Exponential function; Context (archaeology); Computer science; Boolean satisfiability problem; Solver; Time complexity; Constant (computer programming); Function (biology); Algorithm; Mathematics; Theoretical computer science; Mathematical optimization; Jitter","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00512607,0.0009124386,0.0009273748,0.001672046,0.0008650409,0.001866586,0.001757813,0.001380256,0.003113965],"category_scores_gemma":[0.06872711,0.0006321257,0.0008590729,0.002784123,0.002152267,0.004369623,0.001593738,0.003454671,0.0008396363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002027652,"about_ca_system_score_gemma":0.001774031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003854351,"about_ca_topic_score_gemma":0.002837378,"domain_scores_codex":[0.9950933,0.001714229,0.000263082,0.001328346,0.0009951808,0.0006057986],"domain_scores_gemma":[0.9176026,0.06723917,0.003266335,0.007892534,0.00291402,0.00108534],"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":[0.002423751,0.0008651401,0.0648841,0.001438086,0.000432073,0.0005213312,0.0008792125,0.6988919,0.01415054,0.07243251,0.03342837,0.1096529],"study_design_scores_gemma":[0.0001197171,0.0003465635,0.01787718,0.0001388229,0.00007899514,0.0004950469,0.0002777716,0.9227089,0.007785523,0.04495322,0.005150468,0.00006779088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8347362,0.01027812,0.1272233,0.003960146,0.0002765638,0.0001793457,0.005541967,0.003048894,0.01475557],"genre_scores_gemma":[0.9563138,0.001687263,0.03110878,0.0004833915,0.0001970694,0.0002850509,0.007879261,0.000742244,0.001302991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00512607,"threshold_uncertainty_score":0.02710962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3905235528133467,"score_gpt":0.397099776394029,"score_spread":0.006576223580682272,"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."}}