{"id":"W2725171488","doi":"10.1038/nmeth.4346","title":"Principal component analysis","year":2017,"lang":"en","type":"article","venue":"Nature Methods","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":1399,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Principal component analysis; Component (thermodynamics); Computational biology; Computer science; Biology; Artificial intelligence; Physics","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":[0.001192752,0.001606676,0.001292138,0.002680593,0.001076314,0.002786722,0.001147856,0.0009069045,0.02572639],"category_scores_gemma":[0.0048237,0.0006062632,0.001450248,0.003553808,0.0005706659,0.001448346,0.00131588,0.001517555,0.02608203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003926906,"about_ca_system_score_gemma":0.002135722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001584448,"about_ca_topic_score_gemma":0.001889013,"domain_scores_codex":[0.9985535,0.0003039892,0.00007645666,0.0003884067,0.000582334,0.00009535852],"domain_scores_gemma":[0.9980776,0.0003632244,0.0001014334,0.0005095268,0.0008873001,0.00006080933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001272644,0.0001105379,0.001237847,0.0004137374,0.0001588618,0.00007356173,0.0001107182,0.01192934,0.01551914,0.04219648,0.05093777,0.8771846],"study_design_scores_gemma":[0.00007802177,0.0002009728,0.013558,0.0002371799,0.000363032,0.0007069141,0.0002531512,0.4337153,0.04849352,0.09324566,0.4089296,0.0002187419],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003265098,0.0005414589,0.9752961,0.0002134969,0.0003700862,0.0002272747,0.001393545,0.004057392,0.01463555],"genre_scores_gemma":[0.06512202,0.001591088,0.8705544,0.0002530836,0.0003652553,0.0009703555,0.007034973,0.002407994,0.0517007],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02572639,"threshold_uncertainty_score":0.08606333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02683354521457981,"score_gpt":0.4465176621825136,"score_spread":0.4196841169679338,"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."}}