{"id":"W2327365912","doi":"10.1021/nn502858b","title":"Stimuli-Responsive Photoacoustic Nanoswitch for <i>in Vivo</i> Sensing Applications","year":2014,"lang":"en","type":"article","venue":"ACS Nano","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Terry Fox Research Institute; Ontario Institute for Cancer Research; Ontario Ministry of Health and Long-Term Care; Canada Foundation for Innovation; Prostate Cancer Canada","keywords":"Absorbance; Photoacoustic imaging in biomedicine; Materials science; Absorption (acoustics); Photoacoustic effect; In vivo; Molar absorptivity; Photoacoustic spectroscopy; Optoelectronics; Optics; Nanotechnology; Chemistry; Chromatography","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":[0.0002116717,0.0001741025,0.0002076515,0.0001160904,0.00009136205,0.00003328589,0.0001403593,0.00007899299,0.00001442792],"category_scores_gemma":[0.0001494894,0.0001876237,0.00005071372,0.0002426959,0.00003325312,0.00008227183,0.00001769563,0.0001217692,0.00002743119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009197441,"about_ca_system_score_gemma":0.00003477305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001937674,"about_ca_topic_score_gemma":0.00001392208,"domain_scores_codex":[0.9990113,0.000017965,0.0002291761,0.0002266416,0.0001101599,0.0004047339],"domain_scores_gemma":[0.9989607,0.0005990957,0.00002973712,0.0002817995,0.00005823732,0.00007042345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001761418,0.00002101058,0.00004103956,0.0001114061,0.00001996673,0.000002449731,0.000224571,0.02734543,0.9593819,0.0002847982,0.003479762,0.009070083],"study_design_scores_gemma":[0.001452768,0.00003962376,0.00009685411,0.0001168221,0.00007716918,0.00003521829,0.0002229514,0.5779722,0.3253499,0.001647149,0.09241071,0.0005786948],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09500567,0.0001672578,0.8984399,0.00007478009,0.0003457757,0.0008225585,0.00005995619,0.0003574186,0.004726633],"genre_scores_gemma":[0.9921211,0.0000190503,0.006935055,0.0002902045,0.000136468,0.0001189333,0.000009474736,0.00005538336,0.0003143414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8971154,"threshold_uncertainty_score":0.7651072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007484134701413515,"score_gpt":0.2253396201381353,"score_spread":0.2178554854367218,"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."}}