{"id":"W35056265","doi":"10.3390/mi13010101","title":"SATzilla2007: a New & Improved Algorithm Portfolio for SAT","year":2007,"lang":"en","type":"article","venue":"Micromachines","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Portfolio; Computer science; Empirical research; Uncorrelated; Algorithm; Artificial intelligence; Mathematics; Statistics; Economics; Finance","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":[0.002250471,0.002336015,0.001564981,0.002530382,0.0008949434,0.002585262,0.004520955,0.002201232,0.03209336],"category_scores_gemma":[0.006652857,0.001148986,0.00174052,0.002105465,0.0006055604,0.004447366,0.002482847,0.003286974,0.02058503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442001,"about_ca_system_score_gemma":0.003104855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006100644,"about_ca_topic_score_gemma":0.009389068,"domain_scores_codex":[0.9980158,0.0004707479,0.0001499495,0.0004397458,0.0007266955,0.000197086],"domain_scores_gemma":[0.9982104,0.0006582891,0.00009166567,0.0003991086,0.0005490816,0.00009156563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001117867,0.000257042,0.001185786,0.0003738067,0.0002333494,0.00010471,0.00006338133,0.03488122,0.007610527,0.01865541,0.08768485,0.847832],"study_design_scores_gemma":[0.000198666,0.0001592344,0.0003228516,0.00004854624,0.00003794927,0.0001458922,0.00002518606,0.9188278,0.007144798,0.01635411,0.05669396,0.00004091412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003176522,0.000893352,0.9397773,0.000242504,0.0003027574,0.0001802201,0.0009552599,0.04940084,0.005071173],"genre_scores_gemma":[0.0262073,0.0003717761,0.9512496,0.0004857879,0.0001398299,0.0006639746,0.005225799,0.00490725,0.01074866],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03209336,"threshold_uncertainty_score":0.107363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007452344533701575,"score_gpt":0.2535204348574658,"score_spread":0.2460680903237643,"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."}}