{"id":"W4245950408","doi":"10.1109/iembs.2006.4398772","title":"Hardware Accelerator for Genomic Sequence Alignment","year":2006,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Smith–Waterman algorithm; Field-programmable gate array; Computer science; Parallel computing; Software; Sequence (biology); Hardware acceleration; Sequence alignment; Simple (philosophy); Function (biology); Algorithm; Computer hardware; Programming language; Biology","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":[0.0001438038,0.0001723718,0.0001638503,0.00005938437,0.0002033881,0.0004181369,0.001096544,0.00006593606,0.00002487596],"category_scores_gemma":[0.00001678381,0.0001525512,0.00005107706,0.0001403529,0.00004096983,0.0009387252,0.0003584503,0.00008071306,0.00004043749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006668502,"about_ca_system_score_gemma":0.0001104548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003791205,"about_ca_topic_score_gemma":0.000001476979,"domain_scores_codex":[0.998675,0.000003111302,0.0002246548,0.0005282777,0.0002142833,0.0003546728],"domain_scores_gemma":[0.9992469,0.00002030157,0.000116991,0.0002147931,0.0003118838,0.00008916091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000185931,0.0001102861,0.002664302,0.0001116753,0.00001403118,0.00000533911,0.0007096001,0.000007680626,0.2041246,0.7143086,0.03742053,0.04050476],"study_design_scores_gemma":[0.001915806,0.0004324747,0.01097555,0.0002718945,0.00002999892,0.00006085596,0.0002813562,0.3716321,0.1307082,0.1369601,0.3451627,0.00156903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08004923,0.0001281453,0.9132617,0.001097197,0.0003751847,0.0006053298,0.00004677519,0.0003683292,0.004068065],"genre_scores_gemma":[0.900243,0.00001209468,0.09847599,0.0002308479,0.0002114851,0.0001445346,0.00001938594,0.00001187101,0.0006507845],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8201938,"threshold_uncertainty_score":0.6220857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04476237056101543,"score_gpt":0.2654187622972993,"score_spread":0.2206563917362838,"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."}}