{"id":"W3031901586","doi":"10.1021/acsbiomaterials.0c00321","title":"Continuous Formation of Ultrathin, Strong Collagen Sheets with Tunable Anisotropy and Compaction","year":2020,"lang":"en","type":"article","venue":"ACS Biomaterials Science & Engineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Center for Advancing Translational Sciences; Division of Materials Research; National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada","keywords":"Biofabrication; Materials science; Nanoscopic scale; Nanotechnology; Mechanobiology; Collagen fibril; Nanomechanics; Ultimate tensile strength; Tissue engineering; Anisotropy; Biomedical engineering; Composite material; Biophysics; Atomic force microscopy; Anatomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004294051,0.0001354558,0.000214234,0.0001353907,0.00007123367,0.0001508232,0.0002370563,0.00004874679,0.00002114927],"category_scores_gemma":[0.000201326,0.0001190358,0.00001226086,0.0006040083,0.0001843866,0.0005879678,0.00006492284,0.00003632552,0.000007032758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006301618,"about_ca_system_score_gemma":0.00003635532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001522793,"about_ca_topic_score_gemma":5.361757e-7,"domain_scores_codex":[0.9987627,0.00001049533,0.0002559303,0.000184669,0.0004219495,0.0003642276],"domain_scores_gemma":[0.999492,0.00004863995,0.00004441684,0.0001298457,0.00008431489,0.0002007535],"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":[0.00000953409,0.000003923855,0.0001042394,0.0001330513,0.000006080115,0.000003018614,0.0003626117,0.01231468,0.9865583,0.0002220714,0.00002100363,0.0002614662],"study_design_scores_gemma":[0.0002054772,0.0001035829,0.00184264,0.00005839574,0.000005762579,0.00001107522,0.000100735,0.07697649,0.9204072,0.000003424036,0.0001617636,0.0001234468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688367,0.00006231864,0.03031393,0.0000617331,0.0001441923,0.0001881373,0.000009893878,0.0002538475,0.0001292344],"genre_scores_gemma":[0.9946486,0.00003057499,0.005230378,0.000008531718,0.00004931786,0.000008218145,0.000003921091,0.00001919397,0.000001303123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06615112,"threshold_uncertainty_score":0.4854141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01496715156646046,"score_gpt":0.2267960479887392,"score_spread":0.2118288964222788,"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."}}