{"id":"W2404958887","doi":"10.1021/acs.nanolett.5b02123","title":"Controlling Hybridization Chain Reactions with pH","year":2015,"lang":"en","type":"article","venue":"Nano Letters","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada; Directorate-General for Research and Innovation; Associazione Italiana per la Ricerca sul Cancro","keywords":"Concatemer; Chain reaction; Template; DNA; Rational design; Nanotechnology; Chemistry; Biophysics; Polymerization; DNA–DNA hybridization; Nanoreactor; Combinatorial chemistry; Materials science; Biochemistry; Gene; Biology; Polymer; Nanoparticle; Photochemistry; Organic chemistry","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":[0.0001189362,0.0000884797,0.00008502616,0.00003889637,0.00004978088,0.00001663171,0.00005418234,0.0000478026,3.294308e-7],"category_scores_gemma":[0.00004154955,0.00006942456,0.00003626955,0.00009585187,0.00004980108,0.000003647092,0.00001399999,0.00003544721,0.000002383202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001795514,"about_ca_system_score_gemma":0.00002231499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000117246,"about_ca_topic_score_gemma":0.00001219423,"domain_scores_codex":[0.999451,0.00003006785,0.000100375,0.0001925219,0.0001006317,0.000125426],"domain_scores_gemma":[0.9996182,0.000004141431,0.00006566922,0.0001802143,0.00007935307,0.00005243256],"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":[0.00005557511,0.00001313222,0.0003507202,0.000001572684,0.00002740931,0.00000306291,0.000007585631,0.0002100289,0.9962916,0.00001901333,0.002434603,0.0005857139],"study_design_scores_gemma":[0.0004478598,0.0001190579,0.00002978735,0.00001167477,0.00002576447,0.00002327437,0.00004806334,0.00008978726,0.9476516,0.00001182229,0.05139765,0.000143677],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.869647,0.00009669214,0.1267449,0.002282702,0.00006953135,0.0001359974,0.00000634137,0.00008719263,0.0009296883],"genre_scores_gemma":[0.9891524,0.00002019286,0.008715214,0.001593026,0.0001761414,0.00000592408,0.0000803514,0.00001287002,0.0002439306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1195054,"threshold_uncertainty_score":0.2831051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022721896145002,"score_gpt":0.2422328209415709,"score_spread":0.2320056019801209,"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."}}