{"id":"W1553866454","doi":"10.1007/978-3-540-30117-2_4","title":"Hardware Accelerated Novel Protein Identification","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Field-programmable gate array; Software; Key (lock); Process (computing); Identification (biology); Function (biology); Computer hardware; Hardware architecture; Computational biology; Embedded system; Biology; Operating system; Genetics","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":[0.000285049,0.0007028211,0.000563797,0.0004263353,0.0004651563,0.0009725421,0.001642279,0.0005715496,0.01055457],"category_scores_gemma":[0.0003451637,0.0004126649,0.0002743097,0.0005580559,0.0002507283,0.0009955505,0.001039213,0.0008250484,0.00545422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004173259,"about_ca_system_score_gemma":0.0005080555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004758688,"about_ca_topic_score_gemma":0.001354359,"domain_scores_codex":[0.9996363,0.00002805093,0.00001182051,0.00008141444,0.0001927277,0.00004968347],"domain_scores_gemma":[0.9997286,0.00005687373,0.00001855288,0.00008669505,0.00008868064,0.00002057117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00072887,0.0001888784,0.0007031995,0.000222913,0.00004680793,0.000225938,0.00005867296,0.00291188,0.5027705,0.009434033,0.02410709,0.4586012],"study_design_scores_gemma":[0.0000869005,0.0005911506,0.002439786,0.00003024153,0.00006018751,0.001441224,0.00005919666,0.1569525,0.7358922,0.005338357,0.09703881,0.00006932754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08760148,0.003012936,0.8606434,0.0008123489,0.001268726,0.0001943672,0.0007347974,0.02077324,0.02495866],"genre_scores_gemma":[0.234567,0.001149239,0.6862924,0.0005380429,0.0002268644,0.0001661294,0.001966723,0.0005481449,0.07454561],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01055457,"threshold_uncertainty_score":0.0353086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02548243290242062,"score_gpt":0.2679966575271524,"score_spread":0.2425142246247318,"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."}}