{"id":"W7027921559","doi":"","title":"Detecting operons from RNA-seq data
\\nusing a convolutional and recurrent neural
\\nnetwork architecture","year":2023,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"Operon; Genome; Representation (politics); Gene; Function (biology); Convolutional neural network; Bacterial genome size; Model organism","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":[0.0004872507,0.00100254,0.0004318184,0.0007501728,0.0003353524,0.0007491834,0.00115322,0.0006902845,0.00181259],"category_scores_gemma":[0.0009542715,0.000407781,0.0007079543,0.000453626,0.0003075319,0.0006414858,0.0008709075,0.0008667673,0.001291048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007560386,"about_ca_system_score_gemma":0.001401037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01313884,"about_ca_topic_score_gemma":0.02871718,"domain_scores_codex":[0.9996486,0.00003437885,0.00002065812,0.0001394933,0.00009642355,0.00006053796],"domain_scores_gemma":[0.9997188,0.00007000305,0.00003799849,0.00004911657,0.0001013425,0.00002269721],"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":[0.0004009327,0.0003779962,0.01284523,0.0004297423,0.0003155496,0.0004165666,0.0001969497,0.1648526,0.3940418,0.004799676,0.01164829,0.4096745],"study_design_scores_gemma":[0.000008501948,0.00007606143,0.002836615,0.00001535951,0.00003954476,0.00006761419,0.00003578655,0.9124258,0.07871876,0.002305737,0.003440496,0.00002974336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1162131,0.0006354394,0.8585973,0.0005723375,0.0001237368,0.0001704017,0.003012945,0.01608815,0.004586597],"genre_scores_gemma":[0.5126305,0.0007941168,0.4585926,0.0006354894,0.00006774146,0.0003842213,0.01368396,0.0005053037,0.01270604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01313884,"threshold_uncertainty_score":0.02612472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02942130493402596,"score_gpt":0.283524040901655,"score_spread":0.2541027359676291,"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."}}