{"id":"W2584738774","doi":"10.1364/ol.42.000655","title":"Photoacoustic resonance by spatial filtering of focused ultrasound transducers","year":2017,"lang":"en","type":"article","venue":"Optics Letters","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Research Foundation of Korea; Ministry of Education; California HIV/AIDS Research Program","keywords":"Resonance (particle physics); Detector; Optics; Transducer; Attenuation coefficient; Aperture (computer memory); Physics; Wavelength; Photoacoustic spectroscopy; Absorption (acoustics); Ultrasound; Materials science; Photoacoustic effect; Ultrasonic sensor; Photoacoustic imaging in biomedicine; Acoustics; Atomic physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000328422,0.0003640421,0.0002663496,0.0002378785,0.0001289245,0.0005103571,0.000510896,0.0006083623,0.0007109688],"category_scores_gemma":[0.001334323,0.0003057666,0.0003248035,0.0001898019,0.0006156986,0.0007164215,0.0003851624,0.0002405094,0.0003089813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004596094,"about_ca_system_score_gemma":0.000181285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003802273,"about_ca_topic_score_gemma":0.0003223243,"domain_scores_codex":[0.9996222,0.00008734937,0.0000147746,0.00007161179,0.0001609347,0.00004305644],"domain_scores_gemma":[0.9990761,0.0006085981,0.0001412085,0.00006609215,0.00008845618,0.00001939995],"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":[0.00008986077,0.00001268318,0.0001941685,0.00005053854,0.000006763522,0.00009467927,0.00006324503,0.003360391,0.9844667,0.002311407,0.00004693141,0.009302563],"study_design_scores_gemma":[0.00002505429,0.0002874995,0.00122299,0.00001508851,0.00003288598,0.0004259045,0.00003986527,0.1589541,0.8355184,0.001763278,0.001681769,0.00003316958],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6809697,0.001070061,0.3122863,0.0001540917,0.0000416127,0.00003307681,0.00002518014,0.0004109354,0.005009023],"genre_scores_gemma":[0.9625392,0.0004383965,0.03577497,0.00003839026,0.00002338878,0.00002313771,0.0000152919,0.00002480426,0.001122412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007109688,"threshold_uncertainty_score":0.003334701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006954979926339926,"score_gpt":0.2001073223065285,"score_spread":0.1931523423801886,"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."}}