{"id":"W2791618238","doi":"10.1002/pep2.24053","title":"Covalently crosslinked mussel byssus protein‐based materials with tunable properties","year":2018,"lang":"en","type":"article","venue":"Peptide Science","topic":"Silk-based biomaterials and applications","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Centre québécois sur les matériaux fonctionnels","keywords":"Byssus; Glutaraldehyde; Carbodiimide; Materials science; Covalent bond; Chemical engineering; Composite material; Polymer chemistry; Chemistry; Mussel; Organic chemistry","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":[0.0001603865,0.0004713637,0.0001476711,0.0003205188,0.0001126044,0.0002198869,0.0001232131,0.0003391246,0.0005570884],"category_scores_gemma":[0.0001548236,0.0001455421,0.0002042584,0.0001850635,0.0001574493,0.0002208035,0.0001773493,0.0002021628,0.0002047061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001511741,"about_ca_system_score_gemma":0.00006949526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001695829,"about_ca_topic_score_gemma":0.0003551467,"domain_scores_codex":[0.9999104,0.00001526522,0.0000083391,0.00002048395,0.00002340012,0.00002219499],"domain_scores_gemma":[0.9998363,0.00003006419,0.00006466611,0.00001600579,0.00002096648,0.00003185651],"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":[0.00001814875,0.00000621052,0.00005603842,0.00002806517,0.000003876542,0.00002039309,0.000007078203,0.00007323097,0.9991989,0.00003499468,0.00001426724,0.0005387978],"study_design_scores_gemma":[0.00000783635,0.0001165341,0.001470021,0.000004568898,0.00001396354,0.00006611835,0.000009129124,0.0005779496,0.996555,0.00002124975,0.001152393,0.000005196283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952414,0.0009604369,0.002415332,0.00003169593,0.00002879215,0.00001838762,0.0000872377,0.00006623637,0.0011505],"genre_scores_gemma":[0.9963843,0.0004063656,0.001954312,0.00002153184,0.00001027224,0.00001639957,0.00009332851,0.000015386,0.001098275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005570884,"threshold_uncertainty_score":0.001863658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620287468729673,"score_gpt":0.2585123860083875,"score_spread":0.2323095113210908,"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."}}