{"id":"W3037067764","doi":"10.1016/j.chempr.2020.06.012","title":"Molecular Printing with DNA Nanotechnology","year":2020,"lang":"en","type":"article","venue":"Chem","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Nanotechnology; DNA nanotechnology; DNA origami; Scalability; Template; Nanoscopic scale; DNA; 3D printing; Materials science; Inkwell; Computer science; Nanostructure; 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":[0.00003281386,0.0001133564,0.0001125135,0.00001599897,0.00003564119,0.000009607055,0.0001287474,0.0001251772,0.000001331696],"category_scores_gemma":[0.00005456042,0.00009064355,0.00005064544,0.0001317935,0.00008425933,0.000001342657,0.00009153453,0.00008289191,0.00000384436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004703358,"about_ca_system_score_gemma":0.00001791031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.599386e-7,"about_ca_topic_score_gemma":0.000001229958,"domain_scores_codex":[0.9993601,0.000009739402,0.00009547409,0.0003077529,0.0000677814,0.0001591104],"domain_scores_gemma":[0.9996231,0.000001908316,0.00005276647,0.0002204189,0.00004708958,0.00005467261],"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":[0.00001809994,0.000009814801,0.0003113102,0.000007132953,0.00003134897,0.000009760214,0.000007922639,0.000004933061,0.995863,0.00007088456,0.0001546593,0.003511132],"study_design_scores_gemma":[0.0001372922,0.0001681083,0.0000318463,0.000006394875,0.00001531352,0.00001396372,0.00003247936,0.00004513295,0.9812141,0.00002929658,0.01816697,0.0001391204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838561,0.00009882311,0.01331201,0.001545156,0.000007002174,0.00006633771,0.000001668684,0.0001169889,0.0009959065],"genre_scores_gemma":[0.9875904,0.00002152636,0.01109844,0.001126768,0.00006758633,0.000004224513,0.00002317901,0.00001769176,0.00005019754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01801232,"threshold_uncertainty_score":0.3696336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007538502117494178,"score_gpt":0.2286204580105723,"score_spread":0.2210819558930781,"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."}}