{"id":"W2057680553","doi":"10.1109/cibcb.2014.6845519","title":"Shape control of side effect machines for DNA classification","year":2014,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Finite-state machine; Computer science; Task (project management); String (physics); Population; Artificial intelligence; State (computer science); Side effect (computer science); Machine learning; Algorithm; Mathematics; Engineering","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":[0.0007190172,0.0003676821,0.0003260103,0.0002382619,0.000267069,0.0005319684,0.0007568038,0.0006057171,0.00115809],"category_scores_gemma":[0.003728898,0.0002136342,0.000379344,0.0002217157,0.0007668422,0.0007708994,0.0005068849,0.0007289279,0.000380217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004594449,"about_ca_system_score_gemma":0.0002936053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003650209,"about_ca_topic_score_gemma":0.0005658633,"domain_scores_codex":[0.999647,0.00009699847,0.00002277148,0.00009997134,0.0001086655,0.00002450922],"domain_scores_gemma":[0.9982609,0.0009013388,0.0001592743,0.0003384876,0.0002814136,0.00005865193],"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":[0.0002727051,0.0001040282,0.002170883,0.000133853,0.0000280139,0.0001526723,0.000160479,0.5920463,0.1395846,0.02026659,0.0008208607,0.244259],"study_design_scores_gemma":[0.00001093044,0.0001338343,0.0005398196,0.000007226812,0.000009232133,0.00007578436,0.0000149625,0.9445253,0.0458236,0.007123849,0.001721099,0.00001425779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1951622,0.0002542608,0.7990934,0.0001224771,0.00007317104,0.00007130752,0.00005364842,0.001398118,0.003771546],"genre_scores_gemma":[0.8417271,0.00009104442,0.1562858,0.00005329473,0.00001555495,0.00008681018,0.0000936153,0.0001063906,0.001540365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00115809,"threshold_uncertainty_score":0.003874183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011210802458322,"score_gpt":0.2536865594442309,"score_spread":0.2424757569859089,"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."}}