{"id":"W2146916435","doi":"10.1002/chem.201500994","title":"Optimal DNA Templates for Rolling Circle Amplification Revealed by In Vitro Selection","year":2015,"lang":"en","type":"article","venue":"Chemistry - A European Journal","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Rolling circle replication; Amplicon; Template; DNA; Biology; DNA polymerase; Loop-mediated isothermal amplification; Computational biology; Multiple displacement amplification; DNA nanoball sequencing; Polymerase chain reaction; DNA sequencing; Genetics; Molecular biology; Genomic library; Nanotechnology; Base sequence; Gene; DNA extraction; Materials science","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":[0.0009213282,0.0008597738,0.0008767065,0.0006345761,0.0002508897,0.000752446,0.0005260765,0.0006187051,0.0008538785],"category_scores_gemma":[0.002701739,0.0004943457,0.0004119325,0.0007277237,0.0002572489,0.0004819064,0.0003781722,0.0008473764,0.001385118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002210787,"about_ca_system_score_gemma":0.0003589183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001986879,"about_ca_topic_score_gemma":0.0004797534,"domain_scores_codex":[0.9984347,0.0005215502,0.00020799,0.0002790129,0.0003903385,0.0001664071],"domain_scores_gemma":[0.9987074,0.0005227383,0.0002321025,0.0001431107,0.0002947968,0.00009976144],"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":[0.00004984956,0.00002952221,0.0001885738,0.00008372181,0.000006212827,0.00007983026,0.00003156022,0.0003265573,0.9958383,0.0002040496,0.00006953601,0.003092309],"study_design_scores_gemma":[0.000002923818,0.0001238529,0.000202035,0.0000108899,0.00001518865,0.00009831603,0.00002494694,0.001683682,0.9955355,0.00008377317,0.002209927,0.00000894497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7149863,0.007140173,0.2673957,0.0004433588,0.0002633023,0.0007951257,0.00237448,0.001176322,0.005425175],"genre_scores_gemma":[0.7741057,0.004958215,0.2133197,0.0001863977,0.0000576876,0.0005564541,0.00399449,0.0002686758,0.002552705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009213282,"threshold_uncertainty_score":0.004872501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0171224324134701,"score_gpt":0.2646338172660075,"score_spread":0.2475113848525374,"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."}}