{"id":"W2038744481","doi":"10.1111/j.1750-3841.2009.01449.x","title":"High Hydrostatic Pressure Effects on the Texture of Meat and Meat Products","year":2009,"lang":"en","type":"article","venue":"Journal of Food Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Chewiness; Hydrostatic pressure; Cooked meat; Chemistry; Food science; Texture (cosmology); Denaturation (fissile materials); Breakage; Muscle protein; High pressure; Biophysics; Materials science; Skeletal muscle; Composite material; Anatomy; Biology; Thermodynamics","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":[0.0001855947,0.0002092224,0.000167989,0.0002339386,0.0001902543,0.0003825152,0.0001310804,0.0002473184,0.002808147],"category_scores_gemma":[0.0004368736,0.0001761032,0.0002319676,0.0002315009,0.0003078332,0.00025964,0.0002339236,0.000370254,0.0002845877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001445507,"about_ca_system_score_gemma":0.00008380834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007458751,"about_ca_topic_score_gemma":0.0006704103,"domain_scores_codex":[0.999792,0.00003512559,0.000008701154,0.0000284009,0.00009287286,0.00004292311],"domain_scores_gemma":[0.9997444,0.00006105593,0.00006410835,0.00001588749,0.00004814961,0.00006639553],"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":[0.0009302149,0.00004908811,0.002140372,0.0001097264,0.00002094943,0.0001675331,0.0000777856,0.00006004807,0.9890837,0.00006053617,0.00009783596,0.007202245],"study_design_scores_gemma":[0.00004923609,0.003127439,0.2817542,0.00001987617,0.00007248841,0.001174779,0.000336219,0.0007127959,0.7073674,0.0001994916,0.005150169,0.00003581684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946991,0.002284978,0.0007256613,0.00005774422,0.00002473903,0.00001329645,0.0001182468,0.00002128649,0.002054868],"genre_scores_gemma":[0.997145,0.0005432859,0.0004333162,0.00007473199,0.00001937646,0.000009173631,0.0001203477,0.00001858177,0.001636157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002808147,"threshold_uncertainty_score":0.009394228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02558091066813325,"score_gpt":0.2394129180853913,"score_spread":0.213832007417258,"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."}}