{"id":"W1971585008","doi":"10.1016/s0045-2068(02)00018-4","title":"Making AppDNA using T4 DNA ligase","year":2002,"lang":"en","type":"article","venue":"Bioorganic Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"DNA ligase; Chemistry; Sequencing by ligation; DNA; DNA clamp; In vitro recombination; DNA polymerase; Ligase chain reaction; Thermus aquaticus; Circular bacterial chromosome; DNA polymerase II; DNA Ligases; Primase; Biochemistry; Molecular biology; Molecular cloning; Genomic library; Biology; Complementary DNA; Polymerase chain reaction; Gene","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":[0.0007193006,0.001142495,0.0008826984,0.0006037278,0.0006280186,0.001409677,0.001011999,0.001149534,0.003041812],"category_scores_gemma":[0.00125317,0.0008675018,0.0009706694,0.0005589936,0.0004525736,0.001247758,0.00116247,0.002029674,0.006224984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004642495,"about_ca_system_score_gemma":0.0007409324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006040633,"about_ca_topic_score_gemma":0.001092063,"domain_scores_codex":[0.9991432,0.0001003611,0.00007862449,0.0002781781,0.0002064131,0.0001932295],"domain_scores_gemma":[0.9993417,0.0001905957,0.00009027256,0.0001247975,0.0001277113,0.0001249662],"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":[0.000102568,0.00005342066,0.0003154166,0.0001766312,0.00001863813,0.0002334062,0.00009294036,0.000131959,0.9830101,0.000634925,0.0003782973,0.0148518],"study_design_scores_gemma":[0.00001077738,0.00007545366,0.0001266851,0.000006466224,0.00001203432,0.000132732,0.0000239347,0.0001619585,0.9901641,0.0002037548,0.009073206,0.000008832786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5057006,0.002391778,0.4661167,0.0008684909,0.0013022,0.0008151861,0.002639909,0.006265383,0.01389976],"genre_scores_gemma":[0.5720292,0.0029541,0.352362,0.00071007,0.0002194172,0.0008689163,0.01178236,0.001548256,0.05752555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003041812,"threshold_uncertainty_score":0.01017582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03550159440065431,"score_gpt":0.2800782580780526,"score_spread":0.2445766636773983,"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."}}