{"id":"W2391497263","doi":"","title":"The Algorithm About Automatic Search for Differential Path in MD4","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Path (computing); Differential (mechanical device)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008690779,0.0006852761,0.0006742695,0.001759963,0.001108685,0.001169696,0.001148624,0.0009159384,0.008224639],"category_scores_gemma":[0.00278384,0.0003203191,0.0007760119,0.001474021,0.00111144,0.002429648,0.001952393,0.001420978,0.002062795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008154138,"about_ca_system_score_gemma":0.001430862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006399701,"about_ca_topic_score_gemma":0.0005253041,"domain_scores_codex":[0.9988965,0.0001833549,0.0001127083,0.0002402369,0.0004065809,0.0001606179],"domain_scores_gemma":[0.9993444,0.0002144906,0.00005001715,0.0001481113,0.0002174399,0.00002548387],"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":[0.0004956247,0.00009381229,0.001200398,0.0004936219,0.00007249037,0.0003387136,0.0004344154,0.01923398,0.025051,0.372018,0.01374312,0.5668248],"study_design_scores_gemma":[0.0005044182,0.0005390586,0.0009791499,0.0001911728,0.0001350334,0.002812298,0.0002362896,0.2776815,0.1063785,0.5296399,0.08067905,0.0002236516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01203905,0.0003671976,0.9760794,0.0003704721,0.0001592454,0.0002170553,0.000167144,0.001298238,0.009302309],"genre_scores_gemma":[0.2551307,0.0004964477,0.7318019,0.0004214905,0.0001486729,0.000442213,0.0006442144,0.0002749664,0.01063932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008224639,"threshold_uncertainty_score":0.02751416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000120501967051,"score_gpt":0.2934986801943451,"score_spread":0.2834974751746746,"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."}}