{"id":"W1481266406","doi":"10.1002/spe.2327","title":"Stringlish: improved English string searching in binary files","year":2015,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"String (physics); Binary number; Computer science; False positive paradox; Theoretical computer science; Mathematics; Artificial intelligence; Physics; Arithmetic; Theoretical physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005178332,0.0001333445,0.000131598,0.0001000133,0.000120589,0.0003996378,0.0005327519,0.00005711397,0.00000452318],"category_scores_gemma":[0.003179528,0.0001214703,0.00001743529,0.0003494462,0.00005518668,0.005672054,0.0009505694,0.0002877029,0.000004765456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004305783,"about_ca_system_score_gemma":0.0001213128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003843371,"about_ca_topic_score_gemma":0.000009011683,"domain_scores_codex":[0.9986145,0.0001034203,0.0001970924,0.0004666899,0.0002947561,0.0003234858],"domain_scores_gemma":[0.9986644,0.0004274898,0.00008896256,0.0004386901,0.000174014,0.0002063914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004033082,0.0006117244,0.02488426,0.00009253192,0.00002426157,0.001038245,0.3539081,0.0004632739,0.0009125371,0.005627723,0.001268883,0.6107652],"study_design_scores_gemma":[0.00874689,0.002517377,0.03442295,0.00140871,0.00004421513,0.000572548,0.2328495,0.3154423,0.007246715,0.007883257,0.3842905,0.004575077],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6895012,0.002596309,0.3053086,0.0003295086,0.0009542219,0.0002771835,0.000009477606,0.0004410192,0.0005824507],"genre_scores_gemma":[0.826713,0.0001230242,0.1727569,0.0002105838,0.0001122272,0.00004607637,0.000003681433,0.000008402951,0.0000261223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6061901,"threshold_uncertainty_score":0.4953415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02811363975311193,"score_gpt":0.2985223667986366,"score_spread":0.2704087270455247,"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."}}