{"id":"W2136792657","doi":"10.1093/nar/gkp662","title":"HMMConverter 1.0: a toolbox for hidden Markov models","year":2009,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Hidden Markov model; Computer science; Software; Toolbox; Task (project management); Machine learning; Data mining; Probabilistic logic; XML; Markov model; Artificial intelligence; Set (abstract data type); Markov chain; Algorithm; Programming language","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":[0.001804044,0.001805822,0.00161563,0.00224928,0.0006718122,0.001446999,0.003176105,0.001472727,0.07666609],"category_scores_gemma":[0.007073598,0.002322178,0.001543303,0.001759334,0.0004176941,0.002101738,0.002505528,0.002875344,0.04475636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005859481,"about_ca_system_score_gemma":0.001221396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001534496,"about_ca_topic_score_gemma":0.002347114,"domain_scores_codex":[0.9992506,0.00020053,0.00009531023,0.0001769631,0.0002164425,0.00006011966],"domain_scores_gemma":[0.998063,0.001204638,0.0001391597,0.0003155921,0.0002053291,0.0000721663],"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":[0.0006441982,0.0001758688,0.002078442,0.002226953,0.0004424352,0.000783293,0.0005215043,0.03263805,0.01526443,0.01513506,0.4637125,0.4663772],"study_design_scores_gemma":[0.0003475476,0.0001354896,0.004009602,0.0005475771,0.0001826851,0.001698498,0.0001413601,0.3390303,0.03837064,0.08255661,0.5325855,0.000394185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.001365577,0.0006129509,0.725776,0.0001321454,0.000151385,0.000132243,0.01711631,0.2520493,0.002664126],"genre_scores_gemma":[0.01927473,0.001210368,0.8662882,0.0004164179,0.00011772,0.001510873,0.04753948,0.05435121,0.009291013],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07666609,"threshold_uncertainty_score":0.2564736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.072584701986076,"score_gpt":0.3487133995037021,"score_spread":0.2761286975176261,"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."}}