{"id":"W2738214912","doi":"10.1515/sagmb-2016-0066","title":"Comparing the performance of linear and nonlinear principal components in the context of high-dimensional genomic data integration","year":2017,"lang":"en","type":"article","venue":"Statistical Applications in Genetics and Molecular Biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hamilton Health Sciences; Impact; McMaster University; Population Health Research Institute","funders":"Canadian Institutes of Health Research","keywords":"Context (archaeology); Principal component analysis; Nonlinear system; Computer science; Mathematics; Data mining; Statistics; Econometrics; Biology; Physics","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":[0.01391437,0.001028855,0.001262363,0.002077875,0.0005836725,0.002118653,0.0008285689,0.001279789,0.0005863505],"category_scores_gemma":[0.0514208,0.0003053885,0.001198985,0.002573815,0.000894464,0.001925613,0.001463539,0.0009777369,0.0004514914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009333774,"about_ca_system_score_gemma":0.001597679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005721538,"about_ca_topic_score_gemma":0.003641086,"domain_scores_codex":[0.9943862,0.003684128,0.0003925893,0.000544982,0.0007578458,0.0002342654],"domain_scores_gemma":[0.9602357,0.03244295,0.001131318,0.002364448,0.003377623,0.0004480602],"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":[0.003033917,0.0004631382,0.04224616,0.0006662891,0.0008036068,0.0002022919,0.0004395696,0.6800622,0.007820465,0.004745044,0.001501716,0.2580155],"study_design_scores_gemma":[0.0000342015,0.0002104122,0.01012983,0.00002432492,0.00005453487,0.00005450268,0.00009652197,0.9836267,0.003455581,0.001940739,0.0003388042,0.00003398065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6525199,0.003427099,0.3387174,0.000851325,0.0001342566,0.0002552199,0.0003483712,0.001528226,0.002218123],"genre_scores_gemma":[0.8494344,0.0008221139,0.1477042,0.00007049441,0.00003593614,0.0001289637,0.001009379,0.0001472587,0.0006471745],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01391437,"threshold_uncertainty_score":0.07358712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04208724528262083,"score_gpt":0.3307104930972203,"score_spread":0.2886232478145995,"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."}}