{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02412157,0.001726086,0.002704613,0.002345185,0.001854158,0.002711897,0.002698494,0.00265322,0.005281439],"category_scores_gemma":[0.07866598,0.001409486,0.002774842,0.002265743,0.001408743,0.003217369,0.002660789,0.004806481,0.001537261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228717,"about_ca_system_score_gemma":0.001336258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003302312,"about_ca_topic_score_gemma":0.005611862,"domain_scores_codex":[0.9844348,0.01062055,0.0008668888,0.00198719,0.001697833,0.0003926505],"domain_scores_gemma":[0.963661,0.02579212,0.001050712,0.007135774,0.002055472,0.0003050021],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006477063,0.0003326224,0.02094207,0.0007827488,0.002688467,0.001358191,0.0007263873,0.5252503,0.003171284,0.09291188,0.03192488,0.3192635],"study_design_scores_gemma":[0.00004737666,0.00006190594,0.002363394,0.0001175005,0.0002399715,0.0003359634,0.00007829683,0.8875207,0.002330606,0.09996157,0.006901347,0.00004133058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02972429,0.001874672,0.9603572,0.001632156,0.0004755153,0.0001789716,0.0003752552,0.001491122,0.003890773],"genre_scores_gemma":[0.6606721,0.001243775,0.3081189,0.003272395,0.00056812,0.0008428211,0.002595431,0.002166601,0.02051996],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9758784,"threshold_uncertainty_score":0.1275685,"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."}}