{"id":"W3111021351","doi":"10.1002/mame.202000604","title":"A Carbodiimide Coupling Approach for PEGylating GelMA and Further Tuning GelMA Composite Properties","year":2020,"lang":"en","type":"article","venue":"Macromolecular Materials and Engineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canadian Institutes of Health Research","keywords":"Swelling; Materials science; Gelatin; PEGylation; Polyethylene glycol; PEG ratio; Composite number; Carbodiimide; Differential scanning calorimetry; Composite material; Absorption of water; Chemical engineering; Polymer chemistry; Chemistry; 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":[0.0002234558,0.0005516178,0.0001511117,0.0002356495,0.0001187539,0.000170906,0.0002435724,0.0002393706,0.001729498],"category_scores_gemma":[0.0002254056,0.0001887109,0.0001994562,0.0001710676,0.0002116124,0.0002560516,0.0001410889,0.0005891226,0.0003975267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002804264,"about_ca_system_score_gemma":0.000227798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006885473,"about_ca_topic_score_gemma":0.001256689,"domain_scores_codex":[0.999897,0.000009678156,0.00001010348,0.00003360449,0.00003324451,0.0000162775],"domain_scores_gemma":[0.9998767,0.00004035099,0.00002941788,0.00001676906,0.00002100233,0.00001572143],"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":[0.00001122772,0.00001031982,0.00001626439,0.00001859921,0.000001423489,0.00000894136,0.00000637978,0.00004334863,0.9988494,0.00004277628,0.00001292573,0.0009784173],"study_design_scores_gemma":[0.000003856684,0.00003992243,0.0002516106,0.000001122511,0.000002870807,0.00002322638,0.000001625031,0.0003487495,0.9983318,0.000009239607,0.000983809,0.000002278766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8966102,0.002277563,0.09294094,0.0002077855,0.000102405,0.000335268,0.000316812,0.0005818953,0.006627061],"genre_scores_gemma":[0.9319753,0.001378751,0.06026794,0.00008716374,0.00001534235,0.0002268213,0.00028233,0.0001116094,0.005654737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001729498,"threshold_uncertainty_score":0.005785704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01968591716507532,"score_gpt":0.2073634448705554,"score_spread":0.1876775277054801,"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."}}