{"id":"W2086757159","doi":"10.1186/1756-0500-5-183","title":"Design of high-performance parallelized gene predictors in MATLAB","year":2012,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"MATLAB; Computer science; Medicine; Bioinformatics; Biology; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006105679,0.0007535876,0.0004561645,0.0003852169,0.0003605777,0.0008276611,0.001811762,0.0004223374,0.007198455],"category_scores_gemma":[0.001930199,0.0004381342,0.0005054173,0.0003451701,0.0004543235,0.0005639779,0.0005362158,0.0006749462,0.003133137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006690084,"about_ca_system_score_gemma":0.001025164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001537684,"about_ca_topic_score_gemma":0.001243162,"domain_scores_codex":[0.9995704,0.00008120491,0.00003365165,0.0001098586,0.0001459968,0.00005890972],"domain_scores_gemma":[0.9991829,0.000305584,0.00009436626,0.00009867566,0.0002690179,0.00004944888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002107837,0.0003064144,0.007435767,0.0008705356,0.0002661477,0.001138307,0.0006733149,0.5514936,0.1259006,0.03916778,0.01142402,0.2592157],"study_design_scores_gemma":[0.0001333214,0.0001665037,0.0003994459,0.00002440682,0.00003179718,0.0001381533,0.00003396385,0.9086659,0.07352078,0.003075309,0.01378366,0.00002680212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02057703,0.00006844391,0.9632205,0.000092685,0.00004421896,0.0001329134,0.0001676356,0.0126229,0.003073634],"genre_scores_gemma":[0.2124429,0.0001236264,0.7807785,0.00009223642,0.00002670112,0.0007234912,0.0005078856,0.001072635,0.004231932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007198455,"threshold_uncertainty_score":0.02408123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1020596006754574,"score_gpt":0.3541051746602359,"score_spread":0.2520455739847785,"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."}}