{"id":"W2027056044","doi":"10.1016/j.foodres.2005.08.009","title":"Spatial mapping of solid and liquid lipid in confectionery products using a 1D centric SPRITE MRI technique","year":2005,"lang":"en","type":"article","venue":"Food Research International","topic":"Food Chemistry and Fat Analysis","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Advanced Foods and Materials Network","keywords":"Softening; Materials science; Biological system; Computer science; Composite material; Biology","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":[0.0004521417,0.0004051018,0.0002209686,0.0007312009,0.0003883801,0.0007778751,0.0004045482,0.0007932271,0.001369371],"category_scores_gemma":[0.0006037796,0.0004221675,0.0001632188,0.0004821557,0.0006719025,0.0009173322,0.0005153445,0.0007243552,0.0003405798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002658042,"about_ca_system_score_gemma":0.0004148509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453756,"about_ca_topic_score_gemma":0.002656315,"domain_scores_codex":[0.9998808,0.00002665579,0.000004365213,0.00003591354,0.00003057999,0.00002154224],"domain_scores_gemma":[0.9997132,0.0001086968,0.00004964661,0.00002964964,0.00007074419,0.00002792529],"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":[0.0003010895,0.00002196463,0.0004911738,0.000127332,0.00001117662,0.00009529133,0.00007649363,0.0003531967,0.9921943,0.0002962444,0.0001518146,0.005879938],"study_design_scores_gemma":[0.00005572201,0.0003963608,0.01058298,0.0000360636,0.00008441669,0.001877307,0.000203654,0.008541948,0.9729638,0.0004041063,0.004815406,0.00003830985],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8502473,0.002821465,0.1358813,0.0005421967,0.00005389656,0.00009895101,0.0005286101,0.0004682723,0.009357988],"genre_scores_gemma":[0.8621091,0.00299275,0.1263383,0.0002245483,0.00007343529,0.0001500089,0.0005196039,0.0002268588,0.007365574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001453756,"threshold_uncertainty_score":0.004580975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0638151026036196,"score_gpt":0.3170509278477304,"score_spread":0.2532358252441108,"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."}}