{"id":"W4412934941","doi":"10.1007/s00236-025-00495-x","title":"Novel tree-search method for synthesizing SMT strategies","year":2025,"lang":"en","type":"article","venue":"Acta Informatica","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Alliance de recherche numérique du Canada; Georg-August-Universität Göttingen","keywords":"Computer science; Theory of computation; Tree (set theory); Search tree; Theoretical computer science; Programming language; Parallel computing; Search algorithm; Mathematics; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0009473382,0.000124817,0.0001722397,0.0003085467,0.000131542,0.0005239904,0.001251599,0.00006845433,0.000007653503],"category_scores_gemma":[0.001338066,0.0001117666,0.00006918611,0.0005639333,0.00002963828,0.00126986,0.000356154,0.0001863966,0.00002889197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006806564,"about_ca_system_score_gemma":0.0003210447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002297119,"about_ca_topic_score_gemma":0.000002128141,"domain_scores_codex":[0.9987879,0.00001896579,0.0002854539,0.0001629854,0.000302223,0.0004424957],"domain_scores_gemma":[0.995591,0.003569851,0.00003155581,0.0006009692,0.0001325157,0.00007406137],"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":[0.00002169599,0.00008312456,0.0001078821,0.0009786948,0.0001518938,0.000002245888,0.00369326,0.002346895,0.009394422,0.4816117,0.005445162,0.496163],"study_design_scores_gemma":[0.0006621963,0.000104782,0.002425743,0.0001818877,0.00001211148,0.00001386106,0.0007215659,0.9372982,0.02205866,0.003282333,0.03290372,0.0003349857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001200578,0.00002117669,0.9888698,0.001144417,0.0001606771,0.0003158998,0.000003324857,0.0003065452,0.007977566],"genre_scores_gemma":[0.1558188,0.000003901316,0.8435434,0.0001954453,0.00002281837,0.00009551168,0.000002061489,0.00000791294,0.0003101678],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9349512,"threshold_uncertainty_score":0.5052851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03024586843626352,"score_gpt":0.3359139184326752,"score_spread":0.3056680499964117,"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."}}