{"id":"W4390065484","doi":"10.1093/geroni/igad104.0116","title":"REPRESENTATION LEARNING OF PROTEOME DYNAMICS TO CHARACTERIZE ORGANISMIC COMMUNICATION AND INTRINSIC HEALTH","year":2023,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Salivary Gland Disorders and Functions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Proteome; Correlation; Disease; Biology; Computational biology; Psychology; Developmental psychology; Bioinformatics; Physiology; Medicine; Internal medicine; Mathematics","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":[0.001228417,0.0005258657,0.0004568928,0.0009370164,0.0002266262,0.0006389898,0.0004176541,0.0005148344,0.0006995141],"category_scores_gemma":[0.003455659,0.0002020676,0.0005142672,0.0008195435,0.0003139712,0.0007008314,0.0006501182,0.0007590501,0.0001642393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003616969,"about_ca_system_score_gemma":0.0003270853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00205382,"about_ca_topic_score_gemma":0.002281324,"domain_scores_codex":[0.9996281,0.0001222235,0.00001783999,0.000140132,0.00004412599,0.00004755349],"domain_scores_gemma":[0.9989917,0.0005272964,0.0002015299,0.0001239117,0.00009998598,0.00005563115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001550984,0.001175812,0.4129869,0.0004074549,0.001284182,0.0005809268,0.000840701,0.2102781,0.09113949,0.004078799,0.003128245,0.2725483],"study_design_scores_gemma":[0.00001559003,0.0002264568,0.1153272,0.00001628585,0.00006922738,0.0001498846,0.0001152541,0.8747658,0.003606619,0.005084693,0.0005881855,0.00003488841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8333012,0.0005517418,0.1637052,0.0003229679,0.00003468122,0.00006217979,0.0007408335,0.0002588501,0.001022384],"genre_scores_gemma":[0.9844791,0.0001276119,0.01444243,0.00003752821,0.00001961921,0.00004031387,0.0005995157,0.000009824009,0.0002441377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00205382,"threshold_uncertainty_score":0.006496608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744640366199062,"score_gpt":0.3268530772061371,"score_spread":0.2894066735441465,"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."}}