{"id":"W4391219053","doi":"10.1021/acsfoodscitech.3c00387","title":"Investigation of <i>In Situ</i> and <i>Ex Situ</i> Mode of LAB Incorporation and the Effect on Dough Viscoelasticity, Bread Texture, and Overall Physical Quality Postbaking","year":2024,"lang":"en","type":"article","venue":"ACS Food Science & Technology","topic":"Food composition and properties","field":"Nursing","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; McGill University","funders":"Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"In situ; Viscoelasticity; Texture (cosmology); Quality (philosophy); Food science; Materials science; Mode (computer interface); Composite material; Chemistry; Computer science; Physics; Human–computer interaction; Artificial intelligence; Meteorology","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":[0.0005769334,0.0001161253,0.0002387267,0.0003202676,0.0001168203,0.00006481875,0.0001485155,0.00009126728,1.504802e-7],"category_scores_gemma":[0.0001559712,0.00007823006,0.00001770816,0.0007447909,0.002330855,0.0002844275,0.0001470067,0.0002307181,5.188995e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002712876,"about_ca_system_score_gemma":0.00002738034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000963508,"about_ca_topic_score_gemma":0.0001036733,"domain_scores_codex":[0.9989732,0.0001311304,0.0002175024,0.0003090531,0.0002209671,0.0001481703],"domain_scores_gemma":[0.999352,0.0003013659,0.0001023772,0.0001699657,0.00004797787,0.00002635328],"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":[0.0005111067,0.00001716847,0.002174803,0.0001310933,0.000007917688,7.645242e-7,0.001933487,0.00004372512,0.936933,0.04532645,0.000005624203,0.01291479],"study_design_scores_gemma":[0.0007960626,0.003644565,0.00440044,0.0002694433,0.0000268879,0.00002331312,0.0001320391,0.004103295,0.9212947,0.06518213,0.00001553941,0.0001115143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946414,0.0004461811,0.00005602362,0.004201968,0.00008749127,0.0002545822,0.000005697706,0.00006094331,0.0002457081],"genre_scores_gemma":[0.9996858,0.000009401621,0.00007900938,0.0001936956,0.00001413227,0.000008784257,0.00000153421,0.000006157398,0.000001519589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01985568,"threshold_uncertainty_score":0.8588133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707063462867654,"score_gpt":0.2839650719794801,"score_spread":0.2668944373508035,"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."}}