{"id":"W4280545236","doi":"10.21203/rs.3.rs-1562951/v1","title":"Optimization of PVA/TiO2/MMT mixed matrix membrane for food packaging","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Nanocomposite Films for Food Packaging","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Food packaging; Matrix (chemical analysis); Membrane; Food science; Materials science; Composite material; Polymer science; Chemistry","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":[0.000209138,0.0003691903,0.0002446661,0.0002114341,0.0001269049,0.0004339702,0.0001884189,0.0003594526,0.0004565739],"category_scores_gemma":[0.00025398,0.0001783041,0.0003449749,0.0001928418,0.00008969114,0.0002713892,0.0001276437,0.0002897315,0.000181144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002506342,"about_ca_system_score_gemma":0.0001455033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006507458,"about_ca_topic_score_gemma":0.001301215,"domain_scores_codex":[0.9998983,0.00001472507,0.000007382872,0.00002531719,0.00003744636,0.0000168411],"domain_scores_gemma":[0.9999282,0.00001609689,0.00002114083,0.000003944783,0.00002205711,0.00000856413],"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":[0.00003984348,0.00002207641,0.00009535548,0.00005967603,0.000006843446,0.0000252523,0.00000590818,0.0008534296,0.9972786,0.00003272313,0.00001984205,0.001560381],"study_design_scores_gemma":[0.000005485164,0.0001553953,0.0007354069,0.000005214788,0.00001750831,0.0000265894,0.00001479128,0.007676198,0.9907193,0.00001428831,0.0006253758,0.000004587128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889802,0.001405099,0.008266898,0.00005468796,0.00003109436,0.00003211461,0.0001141333,0.00008384571,0.001031768],"genre_scores_gemma":[0.9890229,0.000665851,0.009481832,0.00001311363,0.000004249846,0.00003170683,0.00006549271,0.00002124087,0.0006935605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006507458,"threshold_uncertainty_score":0.001818538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06373877017231765,"score_gpt":0.3902082396411272,"score_spread":0.3264694694688095,"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."}}