{"id":"W2017081471","doi":"10.1016/j.theochem.2003.08.028","title":"A modular numbering system of selected oligopeptides for molecular computations: using pre-computed amino acid building blocks","year":2003,"lang":"en","type":"article","venue":"Journal of Molecular Structure THEOCHEM","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Center for Research Resources; National Institutes of Health; Badan Riset dan Inovasi Nasional","keywords":"Oligopeptide; Computation; Modular design; Peptide; Computer science; Numbering; Residue number system; Visualization; Computational science; Chemistry; Theoretical computer science; Algorithm; Data mining; Programming language; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003593731,0.0004679349,0.0004743132,0.0003239972,0.0005122584,0.0006124031,0.0009068297,0.00030522,0.004337262],"category_scores_gemma":[0.0008477176,0.0003108484,0.0001874116,0.0005603964,0.0002293306,0.0007183555,0.0004421502,0.0005933333,0.000749149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005577788,"about_ca_system_score_gemma":0.0007650878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006097723,"about_ca_topic_score_gemma":0.001272586,"domain_scores_codex":[0.9999198,0.00001574588,0.000007656774,0.00001951293,0.00002314773,0.00001423444],"domain_scores_gemma":[0.9997498,0.00006633494,0.00001964681,0.00007521259,0.00005362135,0.00003533527],"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":[0.001172106,0.0002812265,0.002349376,0.0003700467,0.00006459776,0.000324759,0.0003139806,0.2251453,0.38618,0.06687488,0.004620175,0.3123037],"study_design_scores_gemma":[0.000239995,0.0003890218,0.0006489923,0.00003065992,0.00004131224,0.000111485,0.00005279277,0.7919279,0.1768432,0.01602688,0.01362361,0.00006413973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2839856,0.0001638106,0.7027364,0.0001331631,0.00008823926,0.0002001743,0.0003032384,0.005399068,0.006990342],"genre_scores_gemma":[0.5203408,0.0001447232,0.4764607,0.00006349559,0.0000304323,0.0003967514,0.0003892397,0.0006129659,0.001560845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004337262,"threshold_uncertainty_score":0.01450956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005071963748969783,"score_gpt":0.2365880777724966,"score_spread":0.2315161140235268,"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."}}