{"id":"W2507380695","doi":"10.1038/nmeth.3968","title":"Model selection and overfitting","year":2016,"lang":"en","type":"article","venue":"Nature Methods","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":700,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Overfitting; Selection (genetic algorithm); Computational biology; Model selection; Computer science; Biology; Artificial intelligence; Machine learning; Evolutionary biology; Artificial neural network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003189602,0.0000480989,0.00005182037,0.00002286889,0.00007715759,0.00003374386,0.0001492667,0.00008613395,0.000001601959],"category_scores_gemma":[0.00004686155,0.00002919524,0.00001597368,0.0001770282,0.000009030587,0.0001658063,0.0000746213,0.0001424604,0.000001449808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009363249,"about_ca_system_score_gemma":0.000009392493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.61991e-7,"about_ca_topic_score_gemma":8.852691e-7,"domain_scores_codex":[0.9995359,0.0000566428,0.0000591586,0.0001925057,0.00005665531,0.00009914064],"domain_scores_gemma":[0.9995788,0.0001852521,0.00002829291,0.0001429918,0.00002930691,0.00003536171],"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":[6.351469e-7,0.000003689367,0.00007017406,0.000001180232,0.000001879859,1.08612e-7,0.00001495483,0.00007521735,0.06195602,0.1986304,0.0007687099,0.7384771],"study_design_scores_gemma":[0.0001304128,0.00001319138,0.000820375,0.0000116154,0.000003097838,0.000012966,6.553666e-7,0.8457634,0.02691128,0.1071918,0.01903541,0.0001057483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003598488,0.0002073566,0.9926758,0.002516842,0.00009788419,0.00004388994,3.222205e-7,0.00008579596,0.0007736261],"genre_scores_gemma":[0.2677854,0.00001977089,0.7314329,0.000356574,0.00006128383,0.00000554644,4.965431e-8,0.000002599128,0.0003359072],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8456882,"threshold_uncertainty_score":0.1190547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306701447789608,"score_gpt":0.3722396874107607,"score_spread":0.3491726729328647,"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."}}