{"id":"W4318053700","doi":"10.3390/cells12030411","title":"A Lipidomics- and Transcriptomics-Based Analysis of the Intestine of Genetically Obese (ob/ob) and Diabetic (db/db) Mice: Links with Inflammation and Gut Microbiota","year":2023,"lang":"en","type":"article","venue":"Cells","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Göteborgs Universitet; Stiftelserna Wilhelm och Martina Lundgrens; Canada Excellence Research Chairs, Government of Canada; Fonds De La Recherche Scientifique - FNRS; Université Laval","keywords":"Lipidomics; Oxylipin; Inflammation; Biology; Gut flora; Intestinal permeability; Transcriptome; Lipid signaling; Endocrinology; Proinflammatory cytokine; Internal medicine; Gut–brain axis; Lipid metabolism; Immunology; Gene expression; Biochemistry; Medicine; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002972019,0.0001253384,0.000386085,0.0002987524,0.0000421033,0.00002235247,0.00007615161,0.0001132145,0.00003031937],"category_scores_gemma":[0.00008098131,0.0000835285,0.000074032,0.0007699081,0.0004672676,0.00001991754,0.00005106327,0.0002084002,7.564817e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001797766,"about_ca_system_score_gemma":0.0001257084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000642923,"about_ca_topic_score_gemma":0.00008927529,"domain_scores_codex":[0.9990454,0.00005235561,0.0002903813,0.0002364246,0.0001850895,0.0001903943],"domain_scores_gemma":[0.9992943,0.00006903383,0.00008921033,0.0002581734,0.0001718558,0.0001174667],"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":[0.000210389,0.00004143458,0.01805767,0.0005265385,0.000196608,0.000003394372,0.0004288752,0.0000880872,0.977298,0.0000144414,0.0005467886,0.002587832],"study_design_scores_gemma":[0.003179812,0.0005159252,0.4746373,0.000311834,0.001555839,0.000008809883,0.0002591782,0.03368302,0.4847111,0.00002610875,0.0009434054,0.000167694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951901,0.0005129508,0.00005449041,0.003694833,0.00002616894,0.0004069103,0.00004195795,0.00001111258,0.00006145766],"genre_scores_gemma":[0.9984295,0.0002766721,0.0002650448,0.00008584577,0.00003030387,0.00001153757,0.00002116288,0.00001730052,0.0008626212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4925869,"threshold_uncertainty_score":0.3406193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007937938481988939,"score_gpt":0.2395884356147138,"score_spread":0.2316504971327249,"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."}}