{"id":"W4293330329","doi":"10.1016/j.foodres.2022.111873","title":"Microfluidics in smart packaging of foods","year":2022,"lang":"en","type":"review","venue":"Food Research International","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; McGill University","funders":"","keywords":"Active packaging; Food packaging; Food safety; Food industry; Food quality; Microfluidics; Computer science; Risk analysis (engineering); Biochemical engineering; Business; Engineering; Nanotechnology; Food science; Materials science","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":[0.0007540758,0.0001368896,0.0004146174,0.0008805463,0.00003304756,0.00003000971,0.0004087914,0.0001284986,0.0006991701],"category_scores_gemma":[0.0002136409,0.0001302804,0.0002071645,0.0006124107,0.00005328803,0.00004308201,0.00017469,0.001092916,0.00002977201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003722632,"about_ca_system_score_gemma":0.00007430857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001630219,"about_ca_topic_score_gemma":0.00001029404,"domain_scores_codex":[0.9983522,0.0001387651,0.0004202963,0.0001911731,0.0006350914,0.0002624661],"domain_scores_gemma":[0.9993327,0.0003586076,0.00003520884,0.0001627006,0.00005858315,0.00005214671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003240599,0.00004731283,0.000006645509,0.00400005,0.0002279737,0.00001482404,0.00002452574,0.00002435775,0.0000458347,0.001082781,0.003211622,0.9913108],"study_design_scores_gemma":[0.00007274248,0.0000691268,0.000003397501,0.001204346,0.00001130872,0.00001004904,0.0000147851,0.0007123493,0.0001038079,0.0001991743,0.9974921,0.0001067523],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004451441,0.990633,0.00005529944,0.00003383792,0.0006861603,0.0001938626,0.0001366174,0.00003463812,0.008182039],"genre_scores_gemma":[0.001283804,0.9980698,0.00004305805,0.00000254118,0.0001620779,0.00006000289,0.00008128677,0.00003888867,0.00025849],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9942805,"threshold_uncertainty_score":0.7655422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2315906517900605,"score_gpt":0.419308167171001,"score_spread":0.1877175153809405,"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."}}