{"id":"W2146277109","doi":"10.1002/bip.22700","title":"Convenient synthesis of collagen‐related tripeptides for segment condensation","year":2015,"lang":"en","type":"article","venue":"Biopolymers","topic":"Collagen: Extraction and Characterization","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Chemistry; Tripeptide; Diketopiperazines; Peptide synthesis; Peptide; Condensation; Reagent; Protecting group; Combinatorial chemistry; Morpholine; Solid-phase synthesis; Condensation reaction; Organic chemistry; Extraction (chemistry); Chloroformate; Chromatography; Biochemistry; Catalysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003287488,0.00009115242,0.0001594445,0.00007987384,0.0000573214,0.00002793425,0.0000821084,0.00007138807,0.000533868],"category_scores_gemma":[0.0001657931,0.00008693411,0.00005728244,0.0001464379,0.00007057354,0.0001154122,0.00001466753,0.00001208252,0.0000661076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008489432,"about_ca_system_score_gemma":0.0001164367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003332241,"about_ca_topic_score_gemma":0.000005365274,"domain_scores_codex":[0.9991135,0.00005499086,0.0003159852,0.0001732227,0.0002039844,0.0001383275],"domain_scores_gemma":[0.9992937,0.0000856473,0.000241163,0.0001347768,0.0001506221,0.0000940251],"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":[0.0001383274,0.00005728092,0.000100886,0.00002080067,0.00001126203,5.157243e-7,0.0004471368,0.00001807705,0.9964055,0.0004828527,0.000700028,0.001617334],"study_design_scores_gemma":[0.0005914432,0.00008318137,0.0003749354,0.00001748608,0.00003428816,0.000003310743,0.001317233,0.0003941206,0.9943718,0.0000579251,0.00264984,0.0001044581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960908,0.00008791083,0.0008701479,0.0002872672,0.001030513,0.0004047501,0.00008909909,0.00006054437,0.001078921],"genre_scores_gemma":[0.9982417,0.000008438278,0.0003589173,0.00006110851,0.00003719083,0.00006522003,0.00002749177,0.0000113737,0.001188598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002150814,"threshold_uncertainty_score":0.584548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146813331744299,"score_gpt":0.2633039902984433,"score_spread":0.2318358569810003,"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."}}