{"id":"W1484932675","doi":"10.1007/978-3-642-02777-2_26","title":"A Theoretical Analysis of Search in GSAT","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Heuristic; Algorithm; Distribution (mathematics); Mathematical optimization; Theoretical computer science; Mathematics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00163397,0.0002923262,0.0006557349,0.003242522,0.00007116425,0.0002444888,0.002817177,0.000241618,0.0001319117],"category_scores_gemma":[0.0000906043,0.0002561516,0.0001780528,0.003391219,0.001041411,0.000310554,0.0008257616,0.0007021084,0.00001080946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001776575,"about_ca_system_score_gemma":0.0004651198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001996116,"about_ca_topic_score_gemma":0.000080046,"domain_scores_codex":[0.996516,0.00008308344,0.000569287,0.001074548,0.001197373,0.0005596642],"domain_scores_gemma":[0.9978502,0.0004773036,0.0001305012,0.001116139,0.000271807,0.0001540004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000355062,0.00003334576,0.0001020477,0.00001004919,0.00002037672,0.00002926443,0.0006812743,0.3151607,0.00002238178,0.3978738,0.000001385232,0.2860618],"study_design_scores_gemma":[0.0001408853,0.0001106646,0.0004289901,0.00009810756,0.00001312308,0.000003978844,1.008344e-7,0.8402901,0.0001893229,0.1584569,0.00004266873,0.0002251615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00009021677,0.0001255986,0.9888875,0.001153018,0.0001470577,0.0002581181,0.000003016057,0.00004614841,0.009289252],"genre_scores_gemma":[0.5946256,0.00009879145,0.4039456,0.001041437,0.00006039147,0.000003430235,0.000007305149,0.00001550698,0.0002019414],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5945354,"threshold_uncertainty_score":0.9999891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839180125645525,"score_gpt":0.2793431224071036,"score_spread":0.2609513211506484,"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."}}