{"id":"W4286266835","doi":"10.1016/j.foodres.2022.111710","title":"A mapping approach to assess the evolution of pores during dehydration","year":2022,"lang":"en","type":"article","venue":"Food Research International","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dehydration; Shrinkage; Porosity; Volume (thermodynamics); Biological system; Reduction (mathematics); Process (computing); Thermodynamics; Process engineering; Chemistry; Mechanics; Materials science; Mineralogy; Computer science; Mathematics; Physics; Geometry; Composite material; Engineering","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":[0.0001865844,0.0002909182,0.0001720983,0.000466145,0.0002804759,0.000495351,0.0004085955,0.000442547,0.001165023],"category_scores_gemma":[0.0006390772,0.0002468082,0.0002644917,0.0003744779,0.0002531079,0.0006375791,0.0003142159,0.0003791692,0.0001593064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002432646,"about_ca_system_score_gemma":0.0003161631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001853679,"about_ca_topic_score_gemma":0.001437899,"domain_scores_codex":[0.9999568,0.000004882831,0.000001404481,0.00001699274,0.00001072361,0.000009065101],"domain_scores_gemma":[0.9997419,0.0001174696,0.00003463377,0.00003900778,0.00004387775,0.00002309513],"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":[0.0001954895,0.0001803477,0.01511284,0.0001505964,0.00003543967,0.0002286849,0.0004409483,0.2771807,0.6215428,0.01031982,0.0005303542,0.07408205],"study_design_scores_gemma":[0.000004606872,0.00006813552,0.00551311,0.000004873982,0.000009799177,0.0001229083,0.00007666464,0.9352462,0.05549783,0.002441475,0.0009996404,0.00001490433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5548221,0.0002180647,0.4399984,0.00007948178,0.0000199851,0.00006910332,0.0004006129,0.0008976004,0.003494645],"genre_scores_gemma":[0.9205655,0.0001602016,0.07813668,0.00001005535,0.000003786424,0.00004060529,0.0001518332,0.00007803011,0.0008532016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001853679,"threshold_uncertainty_score":0.003897429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2021737806659039,"score_gpt":0.3370097161402492,"score_spread":0.1348359354743453,"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."}}