{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001705118,0.0004737348,0.000314776,0.0001912341,0.0001097694,0.0004529113,0.0001921579,0.0002910333,0.0006927807],"category_scores_gemma":[0.0001908326,0.000131562,0.0004083528,0.0001797287,0.000155218,0.0003548125,0.0002012228,0.0003198933,0.0001954882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001072131,"about_ca_system_score_gemma":0.0001530512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003443402,"about_ca_topic_score_gemma":0.0006235401,"domain_scores_codex":[0.9998401,0.00002593248,0.0000152565,0.00004224349,0.00004570159,0.000030794],"domain_scores_gemma":[0.9998046,0.00002831094,0.00007932611,0.00001982274,0.00004798441,0.00001995553],"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":[0.00009057616,0.00003754111,0.0004465764,0.00009206845,0.000008045672,0.00002931134,0.00001660047,0.00003995346,0.9965946,0.0000121284,0.00001478944,0.002617787],"study_design_scores_gemma":[0.000004023564,0.0008133077,0.007395727,0.00001164657,0.00005323217,0.00009158219,0.00008061647,0.0005545832,0.9895828,0.00002233727,0.00137942,0.0000107828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925487,0.001878071,0.004378808,0.00005280956,0.00003886412,0.00002678341,0.0001767891,0.00004459088,0.0008545885],"genre_scores_gemma":[0.989799,0.002081824,0.006173566,0.000077817,0.00001918447,0.0000271305,0.0002696419,0.00003936262,0.001512376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006927807,"threshold_uncertainty_score":0.002317607,"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."}}