{"id":"W2172820611","doi":"10.1007/978-3-319-24318-4_6","title":"SATGraf: Visualizing the Evolution of SAT Formula Structure in Solvers","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software Engineering Research","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Boolean satisfiability problem; Maximum satisfiability problem; Heuristic; Branching (polymer chemistry); Theoretical computer science; Solver; Satisfiability; Boolean data type; Heuristics; True quantified Boolean formula; Algorithm; Boolean function; Artificial intelligence; Programming language","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":[0.0006887921,0.00111919,0.0005440792,0.002119752,0.0006045291,0.002912544,0.001665696,0.001200806,0.04577598],"category_scores_gemma":[0.004884196,0.0006064984,0.0008815159,0.001928537,0.0004364384,0.002895561,0.001370415,0.002423588,0.005063252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00080302,"about_ca_system_score_gemma":0.001186623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007116714,"about_ca_topic_score_gemma":0.01272632,"domain_scores_codex":[0.9995763,0.0001277882,0.00002516458,0.00007797456,0.0001458706,0.00004699215],"domain_scores_gemma":[0.9978626,0.001408059,0.0001022364,0.0002120092,0.0003036202,0.0001115832],"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":[0.0009326424,0.0002766337,0.008320312,0.001929996,0.0001881767,0.0006477428,0.003283006,0.1006818,0.02589371,0.1148534,0.3691554,0.3738371],"study_design_scores_gemma":[0.0002087008,0.0001152833,0.003406059,0.000361143,0.00007292676,0.0003298983,0.0006808917,0.7156905,0.02284343,0.1079816,0.1482025,0.0001071165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05638147,0.002636024,0.7135773,0.002484903,0.0007375331,0.0001910295,0.03032807,0.1517456,0.04191809],"genre_scores_gemma":[0.2778912,0.001513464,0.6538847,0.0006012027,0.0001112251,0.0003491972,0.02913353,0.02002764,0.01648779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04577598,"threshold_uncertainty_score":0.1531359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322238015105926,"score_gpt":0.2810982460035222,"score_spread":0.2578758658524629,"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."}}