{"id":"W3108461655","doi":"10.1007/s00216-020-03054-0","title":"Potential impact of tissue molecular heterogeneity on ambient mass spectrometry profiles: a note of caution in choosing the right disease model","year":2020,"lang":"en","type":"review","venue":"Analytical and Bioanalytical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Work & Health; St. Michael's Hospital; University of Toronto; University Health Network","funders":"","keywords":"Concordance; Computational biology; Organoid; Context (archaeology); Profiling (computer programming); Transcriptome; Disease; Mass spectrometry; Biology; Computer science; Bioinformatics; Medicine; Chemistry; Pathology; Genetics; Gene; Gene expression; Chromatography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001623882,0.0005622503,0.001610297,0.0001446879,0.00005228887,0.00004142963,0.000495917,0.000435721,0.0006540648],"category_scores_gemma":[0.0001494785,0.0003597176,0.001070764,0.001011027,0.0004206336,0.00002908396,0.0001919909,0.0008617997,0.000003486844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003124638,"about_ca_system_score_gemma":0.0002889757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002586855,"about_ca_topic_score_gemma":4.156598e-7,"domain_scores_codex":[0.997183,0.00003744142,0.001041616,0.0007827521,0.0005288522,0.0004262913],"domain_scores_gemma":[0.9982511,0.0001267892,0.0003997766,0.0007392209,0.00006697464,0.0004161613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001620063,0.0107564,0.001073758,0.2356783,0.00901765,0.002198261,0.00007598626,0.001616273,0.4401443,0.0708133,0.0007948437,0.226211],"study_design_scores_gemma":[0.002043708,0.0006077172,0.0001490473,0.01946605,0.01835672,0.0001930335,0.00003778428,0.5124922,0.3907712,0.0180334,0.03334236,0.004506675],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01867888,0.9502113,0.01049159,0.001249643,0.00002341334,0.001606204,0.003484777,0.0002042838,0.0140499],"genre_scores_gemma":[0.6451589,0.3535623,0.0005917666,0.00001992854,0.000122236,0.00006167795,0.0002634097,0.00005675766,0.0001630453],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.62648,"threshold_uncertainty_score":0.9998855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662967892653168,"score_gpt":0.3285114280091241,"score_spread":0.3118817490825925,"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."}}