{"id":"W4412316495","doi":"","title":"Low-field NMR-based characterization of plant-based burgers","year":2022,"lang":"en","type":"article","venue":"","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Eesti Teadusagentuur; Fundação de Amparo à Pesquisa do Estado de São Paulo; Natural Sciences and Engineering Research Council of Canada; Fundação de Amparo à Pesquisa do Estado de Goiás; European Commission; Financiadora de Estudos e Projetos; Sihtasutus Archimedes","keywords":"Characterization (materials science); Field (mathematics); Materials science; Mathematics; Nanotechnology; Pure mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002552545,0.0002382069,0.0001685757,0.0004134913,0.0002654904,0.0004100335,0.0002824576,0.0004270856,0.001398907],"category_scores_gemma":[0.000346129,0.0001252961,0.00008617272,0.0002239568,0.0004159906,0.0007058884,0.0001424032,0.0003924325,0.0003958779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002115166,"about_ca_system_score_gemma":0.0001430681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004274888,"about_ca_topic_score_gemma":0.00066309,"domain_scores_codex":[0.9999151,0.00001132561,0.000002343358,0.00002865408,0.0000294182,0.00001304453],"domain_scores_gemma":[0.9998233,0.00007006233,0.00003005637,0.00001985572,0.00004238425,0.00001441811],"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":[0.00003737742,0.0000165639,0.0004025393,0.00002891381,0.00000248407,0.00001879526,0.00005883423,0.0004550623,0.994758,0.0003736542,0.0001001743,0.003747643],"study_design_scores_gemma":[0.00001266162,0.0001604794,0.006295783,0.000009515124,0.00001239857,0.000134054,0.0001523861,0.03124642,0.9578307,0.0008891204,0.003233256,0.00002327271],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.94878,0.0006318865,0.04625969,0.0001666415,0.00002038127,0.00002776091,0.0002308568,0.000255798,0.00362696],"genre_scores_gemma":[0.9790586,0.0003186694,0.01849258,0.00005168169,0.000008860332,0.00002189165,0.0002448016,0.00003245416,0.001770447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001398907,"threshold_uncertainty_score":0.004679859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006376823222511059,"score_gpt":0.2619348613082974,"score_spread":0.2555580380857864,"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."}}