{"id":"W3191800038","doi":"10.1016/j.bpj.2021.08.013","title":"Sequence-dependent mechanics of collagen reflect its structural and functional organization","year":2021,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Collagen: Extraction and Characterization","field":"Materials Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; British Columbia Institute of Technology; Burnaby Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Natural Sciences and Engineering Research Council of Canada","keywords":"Flexibility (engineering); Fibril; Extracellular matrix; Triple helix; Biophysics; Sequence (biology); Basement membrane; Chemistry; Collagen fibril; Matrix (chemical analysis); Flexibility method; Collagen helix; Type I collagen; Crystallography; Materials science; Biochemistry; Cell biology; Stereochemistry; Biology; Stiffness; Mathematics; Composite material","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":[0.0001932637,0.0001919643,0.000111484,0.0002021458,0.0001989409,0.000274794,0.0001642794,0.0002309976,0.00181429],"category_scores_gemma":[0.0005543171,0.0002006763,0.00008567642,0.0002247524,0.000274242,0.0004483188,0.0001494892,0.0003447988,0.0004009377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001247547,"about_ca_system_score_gemma":0.0001626306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004762595,"about_ca_topic_score_gemma":0.001315528,"domain_scores_codex":[0.9999031,0.0000184655,0.000005038096,0.00002280524,0.00003427637,0.00001635483],"domain_scores_gemma":[0.9995863,0.0001714431,0.00009871287,0.00002504973,0.00005871564,0.00005983129],"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":[0.00004366327,0.00000767612,0.00114423,0.000009676809,0.000002534751,0.00001819113,0.00001485297,0.0001275177,0.9978327,0.00006487653,0.00001091428,0.0007231484],"study_design_scores_gemma":[0.000006215187,0.0001701223,0.06299885,0.000005234875,0.0000111561,0.0003550393,0.00007537677,0.005604397,0.9300125,0.0002114546,0.0005388937,0.00001075964],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939582,0.0001956474,0.00482404,0.00003035329,0.000007438457,0.00000721639,0.0001086921,0.00001729693,0.0008510969],"genre_scores_gemma":[0.9970205,0.0001738523,0.001755233,0.00002722392,0.000007176089,0.00001012266,0.0001738266,0.00001615553,0.0008159221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00181429,"threshold_uncertainty_score":0.006069362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841400444110458,"score_gpt":0.2658902761409112,"score_spread":0.2374762716998066,"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."}}