{"id":"W4318776929","doi":"10.1016/j.aca.2023.340909","title":"PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes","year":2023,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Alberta; Canada Foundation for Innovation; Genome Canada","keywords":"Chemistry; Multivariate statistics; Dimension (graph theory); Chemometrics; Data set; Elution; Analytical Chemistry (journal); Biological system; Decomposition; Tensor (intrinsic definition); Algorithm; Chromatography; Statistics; Computer science; Mathematics","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":[0.0001478431,0.0002399684,0.0004226647,0.0001372637,0.00005865675,0.00003015288,0.0007337087,0.000161353,0.0004086025],"category_scores_gemma":[0.00006611487,0.0002090896,0.0001023153,0.0008121392,0.0002174674,0.0001847429,0.0002204706,0.0002738289,0.00002565482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002574637,"about_ca_system_score_gemma":0.00006707843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003870041,"about_ca_topic_score_gemma":0.00007293765,"domain_scores_codex":[0.9982668,0.00001438371,0.00043459,0.0005575523,0.0003258146,0.0004008919],"domain_scores_gemma":[0.9984214,0.0001742819,0.000134647,0.001069709,0.00005334449,0.0001465934],"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":[0.0003475775,0.00083637,0.03625567,0.0005317061,0.0005111451,0.00008500599,0.0001517676,0.000142164,0.9593,0.0004955883,0.001249162,0.000093788],"study_design_scores_gemma":[0.002018376,0.0000427749,0.007283387,0.000280659,0.0002847778,0.00001896836,0.0004697534,0.8368441,0.1516015,0.0003274369,0.0002953353,0.0005329615],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993126,0.000007730631,0.00005089326,0.0003998137,0.000006923612,0.00005733973,0.0001375064,0.0001339163,0.006079894],"genre_scores_gemma":[0.9980677,0.00006606396,0.0005550959,0.00003327465,0.00003981597,0.000008177555,0.0009501073,0.00002935217,0.0002504466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8367019,"threshold_uncertainty_score":0.8526425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02951143145957096,"score_gpt":0.2998883974229289,"score_spread":0.2703769659633579,"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."}}