{"id":"W4387934107","doi":"10.1016/j.jcjd.2023.10.162","title":"CHARACTERIZATION OF HEALTHY AND OBESE ADIPOSE TISSUE REMODELLING BY 3D IMAGING AND SINGLE CELL ANALYSIS","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Cardiovascular Disease and Adiposity","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Medicine; Adipose tissue; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003677999,0.0002722403,0.0003861674,0.0006707442,0.0004022747,0.0009531575,0.0003969016,0.0006739293,0.001179505],"category_scores_gemma":[0.0002715841,0.0003116071,0.0004118933,0.0005262786,0.0004591032,0.0003734937,0.0004022954,0.0007356798,0.0004661994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002582057,"about_ca_system_score_gemma":0.0002444234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001319689,"about_ca_topic_score_gemma":0.002701442,"domain_scores_codex":[0.9997737,0.00001676259,0.00001189899,0.00005833184,0.00009738059,0.00004190688],"domain_scores_gemma":[0.9997752,0.0000586378,0.00003934898,0.00004461652,0.00005326288,0.00002897129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006059271,0.00002184914,0.001124674,0.00003667224,0.000007482946,0.00007271895,0.00009042719,0.0004372647,0.9944623,0.0001955319,0.00007416366,0.003416326],"study_design_scores_gemma":[0.00002443368,0.0002029238,0.07861672,0.00003053631,0.00005610881,0.000939467,0.0005428268,0.03166795,0.881601,0.0008630329,0.005389879,0.00006507346],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9086838,0.001967065,0.08340376,0.000176374,0.00008999336,0.0001075566,0.001584176,0.0003547385,0.003632482],"genre_scores_gemma":[0.9147888,0.001597075,0.07879277,0.0002087842,0.00005575802,0.0002854434,0.001217561,0.0001913264,0.002862481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001319689,"threshold_uncertainty_score":0.003945887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007800411652850187,"score_gpt":0.2123757591105888,"score_spread":0.2045753474577386,"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."}}