{"id":"W4404008725","doi":"10.1016/j.phanu.2024.100419","title":"Exploring the molecular mechanisms and therapeutic benefits of L-theanine in counteracting inflammation","year":2024,"lang":"en","type":"article","venue":"PharmaNutrition","topic":"Neurological Disease Mechanisms and Treatments","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Programs for Assessment of Technology in Health Research Institute","funders":"Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Inflammation; Business; Medicine; Immunology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009383482,0.00007067672,0.00006359079,0.00006980691,0.00004300363,0.00003963755,0.00004914174,0.00001081729,0.00001565045],"category_scores_gemma":[0.00002322759,0.00004948074,0.0000242829,0.0001601089,0.0000146191,0.000210771,0.00002342868,0.00007773085,0.000006761833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001227067,"about_ca_system_score_gemma":0.000003362597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004858036,"about_ca_topic_score_gemma":6.176717e-7,"domain_scores_codex":[0.9993991,0.00007064382,0.0001236891,0.0001771968,0.0001326761,0.00009674253],"domain_scores_gemma":[0.9997405,0.0001453122,0.00002623706,0.00005911905,0.000008543313,0.00002024458],"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":[0.00002860223,0.00005327777,0.000006254938,0.00005510964,0.000003208668,0.00003888516,0.0001079785,0.00009802329,0.9085354,0.06946325,5.432008e-7,0.02160952],"study_design_scores_gemma":[0.000305479,0.00006630534,0.0006036194,0.00008333617,0.00001996171,0.00001479897,0.00001843769,0.007082223,0.9652844,0.02640626,0.00006534661,0.00004980973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979587,0.0005181038,0.0004470355,0.0005699872,0.0001245741,0.0002257615,0.000009918645,0.00004674468,0.00009918508],"genre_scores_gemma":[0.9991826,0.0004855601,0.00003343964,0.0001776311,0.0000208599,0.00008571921,0.000002222416,0.000008243823,0.000003757543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05674908,"threshold_uncertainty_score":0.2017766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1209165425811737,"score_gpt":0.302749098826388,"score_spread":0.1818325562452143,"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."}}