{"id":"W2028020243","doi":"10.1016/j.foodres.2007.12.005","title":"Physicochemical characterization of soymilk after step-wise centrifugation","year":2007,"lang":"en","type":"article","venue":"Food Research International","topic":"Proteins in Food Systems","field":"Agricultural and Biological Sciences","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"","keywords":"Homogenization (climate); Chemistry; Differential scanning calorimetry; Centrifugation; Particle size; Particle-size distribution; Chromatography; Differential centrifugation; Food science; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002131286,0.0003903617,0.0002526346,0.0003179759,0.0002900118,0.000386423,0.0002171608,0.0002301305,0.001451767],"category_scores_gemma":[0.0006222086,0.0001263787,0.0003264906,0.0004015264,0.0002677277,0.0002935919,0.000198055,0.0005925594,0.0004535476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002034704,"about_ca_system_score_gemma":0.0003504585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002332012,"about_ca_topic_score_gemma":0.001757606,"domain_scores_codex":[0.9998453,0.00002030933,0.00001370682,0.0000264518,0.00004952122,0.0000448177],"domain_scores_gemma":[0.9997713,0.00005784477,0.00003708135,0.00001456796,0.00008884876,0.00003048621],"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":[0.000231157,0.00003042548,0.001049251,0.00004708914,0.00001359537,0.0001550879,0.00009370725,0.00007434164,0.9962254,0.00003832247,0.00009299221,0.001948755],"study_design_scores_gemma":[0.00001099216,0.0003257564,0.06094019,0.00001893812,0.00005006419,0.000303855,0.0002805299,0.0008779067,0.9340326,0.00007123459,0.003063398,0.00002450448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922579,0.0009941707,0.003616193,0.0001874914,0.00006131361,0.00004454373,0.0007043683,0.00006745772,0.002066617],"genre_scores_gemma":[0.9887539,0.0006281615,0.003030777,0.0001299757,0.00001570963,0.00003693417,0.002156697,0.00007386717,0.005173905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002332012,"threshold_uncertainty_score":0.004856646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05637591098788441,"score_gpt":0.319920759589532,"score_spread":0.2635448486016476,"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."}}