{"id":"W4400047395","doi":"10.1007/s11694-024-02716-2","title":"Dual system to develop fish gelatin films with improved water resistance properties: enzymatic cross-linking and multilayer lamination","year":2024,"lang":"en","type":"article","venue":"Journal of Food Measurement & Characterization","topic":"Silk-based biomaterials and applications","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs","keywords":"Gelatin; Lamination; Water resistance; Dual (grammatical number); Fish <Actinopterygii>; Enzyme; Materials science; Chemistry; Chemical engineering; Food science; Composite material; Fishery; Biochemistry; Biology; Engineering; Art","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002489459,0.0006421951,0.0002008086,0.0002355451,0.0001512854,0.000312315,0.0002059819,0.0004266001,0.001245139],"category_scores_gemma":[0.0001699719,0.0002352136,0.0002630175,0.0001413535,0.0001561234,0.0004003732,0.0003595721,0.0006151147,0.00050218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224085,"about_ca_system_score_gemma":0.0001329111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002391174,"about_ca_topic_score_gemma":0.0005931564,"domain_scores_codex":[0.9998455,0.00002090876,0.00001344637,0.00005090081,0.00003466741,0.00003456388],"domain_scores_gemma":[0.9998589,0.0000179078,0.00005321641,0.00001663663,0.00002483032,0.00002863638],"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":[0.00001066425,0.000006368377,0.00001718411,0.00001414685,0.000002157689,0.000008433681,0.000005585726,0.00001038739,0.9995327,0.00001890723,0.00000909876,0.0003643972],"study_design_scores_gemma":[0.000003618308,0.00005428909,0.0001824153,0.000001788398,0.000007639006,0.00003514674,0.000004152682,0.0002689722,0.998838,0.000004774764,0.0005967676,0.00000248552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577549,0.001336068,0.03799236,0.0001748265,0.00009813174,0.00008872298,0.000185601,0.0003031617,0.002066269],"genre_scores_gemma":[0.9608809,0.0007540245,0.03161469,0.0001311386,0.00002417174,0.0001355073,0.0002336862,0.00007546342,0.006150519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001245139,"threshold_uncertainty_score":0.004165411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02901836230866685,"score_gpt":0.235162750336044,"score_spread":0.2061443880273771,"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."}}