{"id":"W2141678038","doi":"10.1109/isit.2004.1365091","title":"Short-cycle-free interleaver design for increasing minimum squared euclidean distance","year":2004,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Euclidean distance; Algorithm; Graph; Computer science; Mean squared error; Probability of error; Euclidean geometry; Minimum distance; Factor graph; Error detection and correction; Mathematics; Decoding methods; Theoretical computer science; Discrete mathematics; Statistics; Artificial intelligence","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":[0.000437575,0.0005444351,0.0003222214,0.0005400422,0.0003142725,0.0004919331,0.0006813003,0.0003461087,0.001969372],"category_scores_gemma":[0.003568659,0.000200122,0.0001689784,0.0005994036,0.0004072645,0.0009421616,0.0004579777,0.000625796,0.0004989412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005178252,"about_ca_system_score_gemma":0.0008329751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009135781,"about_ca_topic_score_gemma":0.00219621,"domain_scores_codex":[0.9992923,0.0001368487,0.00007003861,0.0001205031,0.0003108669,0.00006940045],"domain_scores_gemma":[0.997846,0.0007406762,0.0003261107,0.0003320818,0.0006707284,0.00008434119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006901436,0.0001557376,0.001630481,0.0003330291,0.0000697639,0.0002321378,0.0002569518,0.1880649,0.2574849,0.1902986,0.003056897,0.3577265],"study_design_scores_gemma":[0.00009629199,0.0005295158,0.00073048,0.00005966255,0.00005840705,0.0004412268,0.0000428842,0.6513176,0.2617621,0.06725636,0.01763812,0.00006730264],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02967552,0.0001626579,0.966614,0.0000643844,0.00003033749,0.00003543533,0.00003451159,0.0004257502,0.002957284],"genre_scores_gemma":[0.5542194,0.0002801586,0.4411135,0.000133375,0.00003352005,0.0001184368,0.0001229281,0.0002336091,0.00374515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001969372,"threshold_uncertainty_score":0.006588161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224094315140034,"score_gpt":0.2800949596242964,"score_spread":0.2478540164728961,"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."}}