{"id":"W2753413310","doi":"10.1002/pro.3286","title":"Engineered, highly reactive substrates of microbial transglutaminase enable protein labeling within various secondary structure elements","year":2017,"lang":"en","type":"article","venue":"Protein Science","topic":"Blood properties and coagulation","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; PROTEO; Centre in Green Chemistry and Catalysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Lysine; Tissue transglutaminase; Glutamine; Fluorophore; Biochemistry; Protein secondary structure; Substrate (aquarium); Active site; Protein engineering; Protein structure; Reactivity (psychology); Protein design; Enzyme; Stereochemistry; Combinatorial chemistry; Amino acid; Fluorescence; Biology","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":[0.0005450482,0.0001646225,0.0002530678,0.0001030588,0.0004708793,0.0001223325,0.0003990119,0.00008261469,0.00006646714],"category_scores_gemma":[0.0001952983,0.0001303761,0.00004340621,0.0001833885,0.0004526327,0.0005760307,0.00006959618,0.000267552,0.000003818864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005900066,"about_ca_system_score_gemma":0.0005361424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004659823,"about_ca_topic_score_gemma":0.00005466688,"domain_scores_codex":[0.99847,0.00001976742,0.0003443074,0.0003895924,0.0004449869,0.0003313296],"domain_scores_gemma":[0.9987479,0.000005947153,0.0002966185,0.0005397668,0.0002907987,0.0001189059],"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":[0.0001626201,0.00005946303,0.0005556191,0.0001701377,0.0000184946,0.00001063972,0.0007148514,0.00002328867,0.9933577,0.0003354658,0.000002654066,0.004589113],"study_design_scores_gemma":[0.001131832,0.0003264866,0.004052886,0.0003252093,0.00003458722,0.00001941374,0.000120618,0.0007470166,0.9923723,0.0006397975,0.00008046534,0.0001493411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973292,0.0001525996,0.0001086387,0.0003322497,0.0001049526,0.001368749,0.00002957857,0.00003128383,0.0005427095],"genre_scores_gemma":[0.9873568,0.000001481264,0.01202351,0.00003134949,0.00007039778,0.0000412013,0.000006322754,0.00001533571,0.0004535675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01191488,"threshold_uncertainty_score":0.5316582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0148107714537577,"score_gpt":0.2481774866604253,"score_spread":0.2333667152066676,"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."}}