{"id":"W4401214288","doi":"10.69645/vcej7127","title":"Improving mitochondrial phenotypes with pharmaceuticals","year":2024,"lang":"en","type":"article","venue":"˜The œbiomedical & life sciences collection.","topic":"Mitochondrial Function and Pathology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Phenotype; Mitochondrial DNA; Computational biology; Biology; Genetics; Gene","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":[0.0016474,0.001064008,0.001253553,0.001742246,0.0008711789,0.001610072,0.0009402591,0.000848599,0.02135136],"category_scores_gemma":[0.001308414,0.0003319498,0.001187179,0.00113656,0.0005710454,0.0005029291,0.001385791,0.001766816,0.009631523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072477,"about_ca_system_score_gemma":0.002390572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002216699,"about_ca_topic_score_gemma":0.006447143,"domain_scores_codex":[0.9989102,0.0001816686,0.0001251996,0.0001831549,0.0004292053,0.0001706698],"domain_scores_gemma":[0.9988492,0.00008851573,0.0001057915,0.0002644891,0.0003758553,0.0003162388],"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":[0.003888894,0.001829184,0.005043468,0.0006548108,0.0002147373,0.000630996,0.0001311261,0.0006362594,0.5910336,0.004853437,0.07973961,0.3113439],"study_design_scores_gemma":[0.002297729,0.007510684,0.04329804,0.0002851313,0.0004701258,0.004684169,0.0001137013,0.001282836,0.5833982,0.001537112,0.3550086,0.0001136497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.549517,0.03626938,0.07097317,0.02724956,0.005469042,0.006587079,0.09744842,0.009711078,0.1967753],"genre_scores_gemma":[0.5513345,0.04287737,0.08723765,0.005642023,0.001003652,0.003477166,0.1147853,0.001836678,0.1918056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02135136,"threshold_uncertainty_score":0.07142746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01756552581875283,"score_gpt":0.2887597792609005,"score_spread":0.2711942534421477,"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."}}