{"id":"W2105555168","doi":"10.1155/2010/937123","title":"Regulation of PPAR<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>γ</mml:mi></mml:math>Coactivator-1<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>α</mml:mi></mml:math>Function and Expression in Muscle: Effect of Exercise","year":2010,"lang":"en","type":"article","venue":"PPAR Research","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algorithm; Mitochondrial biogenesis; Coactivator; Machine learning; Artificial intelligence; Bioinformatics; Computer science; Biology; Function (biology); Transcription factor; Gene; Genetics","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":[0.0002389685,0.0003380901,0.0003153674,0.0003892762,0.0003743453,0.0009751093,0.0004614477,0.000491211,0.01493661],"category_scores_gemma":[0.0002253143,0.0002299356,0.0005022053,0.0005482736,0.0002344289,0.0003610148,0.0005693115,0.0009565436,0.006372504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006421525,"about_ca_system_score_gemma":0.0005094211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002003677,"about_ca_topic_score_gemma":0.003033685,"domain_scores_codex":[0.9996915,0.00003774661,0.00002540705,0.0001010856,0.00008221942,0.00006214059],"domain_scores_gemma":[0.9999045,0.00001666723,0.00002425637,0.00001515554,0.00002480296,0.00001464561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005561514,0.0001463185,0.001117564,0.0003721307,0.00003190508,0.0001878257,0.000149309,0.000393446,0.9376014,0.004230556,0.00649454,0.04871899],"study_design_scores_gemma":[0.0001229091,0.0004597983,0.04136775,0.0001707355,0.00009007793,0.001118377,0.0002417594,0.002542215,0.6851972,0.002565836,0.2660663,0.00005705196],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.68464,0.04992583,0.08691726,0.00611995,0.001837209,0.0003700898,0.0304592,0.003968668,0.1357618],"genre_scores_gemma":[0.7915875,0.02603226,0.02034966,0.002248631,0.0001901935,0.0005033169,0.02564458,0.001286622,0.1321573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01493661,"threshold_uncertainty_score":0.04996789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0250097858794507,"score_gpt":0.2897744791504246,"score_spread":0.2647646932709739,"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."}}