{"id":"W2486459361","doi":"10.1039/c6cc04970b","title":"DNA micelles as nanoreactors: efficient DNA functionalization with hydrophobic organic molecules","year":2016,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Qatar National Research Fund; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Nanoreactor; DNA; Micelle; Oligonucleotide; Nanopore; Surface modification; Conjugated system; Chemistry; Polymer; Molecule; Combinatorial chemistry; Drug delivery; DNA nanotechnology; Reactivity (psychology); Nanotechnology; Biophysics; Materials science; Organic chemistry; Nanoparticle; Biochemistry; Biology","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":[0.00006749913,0.0001522508,0.0001172491,0.00004167791,0.0001333002,0.00001701436,0.0004042273,0.0001240907,0.00001011309],"category_scores_gemma":[0.00009718409,0.00009875205,0.00007229435,0.0001932404,0.0003202551,0.000003925029,0.0002245332,0.0000674318,0.0000204221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004048314,"about_ca_system_score_gemma":0.00005752595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005019299,"about_ca_topic_score_gemma":0.0000140027,"domain_scores_codex":[0.999186,0.00005298154,0.0001848469,0.0002870237,0.0001280483,0.0001611266],"domain_scores_gemma":[0.9984968,0.00004505525,0.0001015825,0.001114596,0.0001700179,0.0000719845],"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":[0.00003192899,0.0001121224,0.0001083112,0.000002639697,0.00003982729,3.03358e-7,0.000009343561,0.000001031559,0.9986132,0.0002172365,0.0002894378,0.0005745979],"study_design_scores_gemma":[0.0002283464,0.00006743846,0.00005829472,0.00003874926,0.00003902066,0.00001710906,0.00002897631,0.00003712592,0.9833338,0.000175556,0.01579411,0.0001814274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895983,0.0003277503,0.007352417,0.001149606,0.00001370493,0.0001177184,0.00001593577,0.00008394477,0.001340591],"genre_scores_gemma":[0.9945123,0.0003484279,0.004120057,0.0001916266,0.00004814163,0.00002118755,0.0003281444,0.0000249916,0.0004050765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01550467,"threshold_uncertainty_score":0.4026991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00881099915439716,"score_gpt":0.2462079832003748,"score_spread":0.2373969840459777,"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."}}