{"id":"W3110692448","doi":"10.1038/s41598-020-78924-9","title":"Cu-chitosan nano-net improves keeping quality of tomato by modulating physio-biochemical responses","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Nanocomposite Films for Food Packaging","field":"Materials Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science Research and Technology; Department of Science and Technology, Ministry of Science and Technology, India; Canadian Institute of Steel Construction","keywords":"Chitosan; Ascorbic acid; Respiration rate; Polyphenol oxidase; Chemistry; Postharvest; Relative humidity; Food science; Horticulture; Shelf life; Respiration; Botany; Biochemistry; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001575911,0.0002390692,0.000478749,0.00008778641,0.000343203,0.0003214003,0.0003815823,0.00008854952,0.00008493966],"category_scores_gemma":[0.0007467673,0.0002325967,0.0001693953,0.0006280662,0.000399833,0.0003849595,0.000358721,0.0001278388,0.00002415489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000271043,"about_ca_system_score_gemma":0.0001323862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001005455,"about_ca_topic_score_gemma":0.000001807009,"domain_scores_codex":[0.9959497,0.0001874995,0.001226947,0.001193859,0.0009354101,0.0005065745],"domain_scores_gemma":[0.9976234,0.0001275407,0.000937991,0.0009324512,0.0001200977,0.0002585444],"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":[0.00005470834,0.0000523055,0.001023592,0.000140773,0.000008734291,0.00002166434,0.0009256166,0.00003091261,0.9927785,0.00002288786,0.004795847,0.0001444253],"study_design_scores_gemma":[0.0001353812,0.00004350252,0.0005084386,0.0000759604,0.00001223835,0.00003119557,0.0001586683,0.000443691,0.9973097,0.0004778942,0.0005362513,0.0002670494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961907,0.0001992353,0.000191567,0.0002740945,0.002105357,0.0003210107,0.00003483974,0.0002170945,0.0004660722],"genre_scores_gemma":[0.9960728,4.694359e-7,0.003497694,0.00009643357,0.00009143044,0.00001221636,0.0000597677,0.00002903062,0.0001401692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004531196,"threshold_uncertainty_score":0.9485018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372357637388149,"score_gpt":0.2854019121484739,"score_spread":0.2616783357745924,"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."}}