{"id":"W2330955477","doi":"10.1021/acs.nanolett.6b00156","title":"Programmable Quantitative DNA Nanothermometers","year":2016,"lang":"en","type":"article","venue":"Nano Letters","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Canada","keywords":"Nanomaterials; Nanoelectronics; Nanotechnology; Robustness (evolution); Nanofluidics; Materials science; 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":[0.00004554601,0.0001195765,0.00009835568,0.00009841478,0.00004210895,0.00002266752,0.00009554268,0.00004259921,0.0001278505],"category_scores_gemma":[0.00001314593,0.00007962222,0.00006401729,0.0001567987,0.00004863909,0.00009020066,0.000009861292,0.00003317642,0.0001182647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004434369,"about_ca_system_score_gemma":0.000004540793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006280898,"about_ca_topic_score_gemma":0.000004023886,"domain_scores_codex":[0.9993923,0.00001717628,0.0001078727,0.0001352502,0.0001088683,0.0002385106],"domain_scores_gemma":[0.99972,0.0000301519,0.00001601789,0.0001758196,0.00001266803,0.00004534447],"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":[0.00000569296,0.000003132855,0.00009969414,0.000008746539,0.00003904487,0.000006917313,0.00003968327,0.00007758317,0.9743277,0.0003375424,0.00962282,0.01543141],"study_design_scores_gemma":[0.0007545073,0.00007171839,0.001161353,0.00005612258,0.0000221999,0.00001425172,0.0000183771,0.00005271368,0.8159944,0.0001479525,0.1813196,0.000386789],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635729,0.0001637775,0.03297365,0.001026629,0.0006365164,0.0001580308,0.000009526867,0.0003553338,0.001103616],"genre_scores_gemma":[0.9952242,0.00002189414,0.003889334,0.000515516,0.00004133624,0.00002999384,0.000002103837,0.00004011024,0.000235471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1716968,"threshold_uncertainty_score":0.32469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007663733933929996,"score_gpt":0.2000177251130704,"score_spread":0.1923539911791404,"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."}}