{"id":"W2756910067","doi":"10.1016/j.foodchem.2017.09.089","title":"Thermogravimetric analysis for rapid assessment of moisture diffusivity in polydisperse powder and thin film matrices","year":2017,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Agriculture and Agri-Food Canada","funders":"","keywords":"Thermal diffusivity; Moisture; Thermogravimetric analysis; Materials science; Thermodynamics; Water content; Composite material; Chemistry; Geology; Geotechnical engineering; Organic chemistry; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001794711,0.00009754127,0.0002104025,0.00001667626,0.0001631464,0.00006048352,0.0002232862,0.00009923435,0.0000458109],"category_scores_gemma":[0.00006552746,0.00004142596,0.0001224807,0.0001997248,0.00004439177,0.00005729504,0.00007112917,0.00008310949,9.411971e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001077349,"about_ca_system_score_gemma":0.00000621751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004130772,"about_ca_topic_score_gemma":0.0002706661,"domain_scores_codex":[0.9993527,0.00001069047,0.0001456213,0.000225773,0.0001157149,0.0001495282],"domain_scores_gemma":[0.9995613,0.00008561532,0.0001584862,0.0001113445,0.00003511113,0.00004820793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003318533,0.0002037483,0.1280165,0.00009787375,0.0002230332,0.000001088472,0.0001230474,0.0001323367,0.8527058,0.00002618007,0.00003946543,0.01839774],"study_design_scores_gemma":[0.0003853026,0.0001668176,0.9202085,0.00002863811,0.0001709015,0.000001074566,0.0006157098,0.004899079,0.07301193,0.000138651,0.0001546506,0.0002187644],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980379,0.0005354322,0.00000893192,0.0002159131,0.0000170248,0.00007851953,0.0001078652,0.00001157579,0.0009867847],"genre_scores_gemma":[0.9995636,0.00007092277,0.0001582269,0.00001393598,0.00005556286,0.000008635596,0.00003756113,7.494922e-7,0.00009082022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7921919,"threshold_uncertainty_score":0.1689302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02398942106845375,"score_gpt":0.2658231673013062,"score_spread":0.2418337462328524,"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."}}