{"id":"W4285203758","doi":"10.1109/access.2022.3174192","title":"An Interactive Interpreter for Two Dimensional Lucid","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Lucid dream; Interpreter; Computer science; Human–computer interaction; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001649904,0.00010703,0.000110342,0.0001413326,0.0002403145,0.0001551218,0.001506297,0.00001625929,0.00004839159],"category_scores_gemma":[0.00002057711,0.0001101603,0.00006244707,0.000221984,0.00002141291,0.001955558,0.0005557304,0.000182325,0.00000353606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250676,"about_ca_system_score_gemma":0.00003324565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002497992,"about_ca_topic_score_gemma":0.000006398305,"domain_scores_codex":[0.998969,0.00007145552,0.0001577225,0.0004147312,0.0002002216,0.0001868665],"domain_scores_gemma":[0.9991333,0.0001369682,0.0001033894,0.0004726996,0.00009654342,0.0000571274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001031327,0.001074351,0.0006424661,0.00005168243,0.0001585598,0.0001252675,0.004274359,0.06669021,0.1906804,0.02148413,0.03093607,0.6828512],"study_design_scores_gemma":[0.0007391782,0.001023579,0.0001738995,0.00001511844,0.000007738994,0.0001036888,0.00003653314,0.241819,0.6677892,0.06741025,0.02037094,0.0005109289],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0318493,0.000008842305,0.9654624,0.000193196,0.00141535,0.00030725,0.00001352542,0.0005307719,0.0002193314],"genre_scores_gemma":[0.9556504,2.06406e-7,0.04172614,0.001844771,0.00007936262,0.0005811085,0.000004464992,0.00001462304,0.00009885051],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9238012,"threshold_uncertainty_score":0.4492208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046818117532629,"score_gpt":0.3648581318169308,"score_spread":0.3443899506416045,"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."}}