{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001082322,0.000194136,0.0002326168,0.00004272992,0.0001585885,0.00008989075,0.0003972662,0.00005739856,0.0000627976],"category_scores_gemma":[0.00008348447,0.0002152355,0.00007580912,0.00003523358,0.0001685368,0.0001695287,0.00001755828,0.0001970076,0.000006371243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005828406,"about_ca_system_score_gemma":0.00001323464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001032532,"about_ca_topic_score_gemma":0.000007485722,"domain_scores_codex":[0.9989931,0.000008833457,0.0002406273,0.0001885108,0.0001996053,0.000369321],"domain_scores_gemma":[0.9992125,0.000110726,0.00007495502,0.000506639,0.00001954314,0.00007561348],"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":[0.00001005659,0.0000120237,0.0001982131,0.00009125346,0.00003792209,0.00001337108,0.0002854135,0.01112017,0.9815472,0.000006100244,0.003925044,0.002753171],"study_design_scores_gemma":[0.002321606,0.00006021805,0.005165441,0.0003653827,0.0001922526,0.00004449704,0.0001306481,0.3435856,0.6408841,0.00003279302,0.006109775,0.001107655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7828671,0.0001755487,0.2120972,0.0001954704,0.0007124078,0.0001594404,0.0001430558,0.0001332618,0.00351647],"genre_scores_gemma":[0.994917,0.00008530745,0.004653904,0.0001250266,0.00008776777,0.00001098562,0.000009228463,0.00005196612,0.00005875807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3406632,"threshold_uncertainty_score":0.8777049,"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."}}