{"id":"W2059455161","doi":"10.1117/12.2082439","title":"The study of photoacoustic imaging without nanoparticles as a contrast agent for anti-body drug monitoring","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Materials science; Absorption (acoustics); SIGNAL (programming language); Nanoparticle; Wavelength; Contrast (vision); Photoacoustic imaging in biomedicine; Doxorubicin; Excitation; Optics; Biomedical engineering; Optoelectronics; Nanotechnology; Computer science; Physics; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003434235,0.0002747487,0.0001987692,0.0002107755,0.0001364241,0.0003824953,0.0003212987,0.0005101531,0.0004313105],"category_scores_gemma":[0.0004736032,0.0002200797,0.0001920916,0.000176476,0.0004006189,0.0009993383,0.0001891319,0.0005551081,0.0001462107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003579359,"about_ca_system_score_gemma":0.0001960843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005173346,"about_ca_topic_score_gemma":0.0003887109,"domain_scores_codex":[0.9997793,0.0000378954,0.000006870355,0.00008160348,0.0000655773,0.000028821],"domain_scores_gemma":[0.9997774,0.000103681,0.00004510433,0.00001243385,0.00004122438,0.00002018782],"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":[0.00002981294,0.0000251778,0.0001763514,0.0001048999,0.000004672908,0.00007663642,0.00004155554,0.0002295385,0.9937184,0.001123576,0.0000724059,0.004396903],"study_design_scores_gemma":[0.000007465206,0.0002580118,0.0007893659,0.00001001735,0.00001457229,0.0002962487,0.0000273449,0.009399286,0.9848499,0.0001990958,0.004139138,0.000009495702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8499048,0.02712649,0.1122427,0.001136296,0.000181894,0.0001337107,0.00005960785,0.0001491343,0.009065398],"genre_scores_gemma":[0.9547296,0.007905064,0.0323916,0.000262803,0.00006808739,0.00009232874,0.00004831402,0.00002430353,0.004478001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005173346,"threshold_uncertainty_score":0.002597034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220187125738496,"score_gpt":0.2417941197478481,"score_spread":0.2295922484904631,"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."}}