{"id":"W2065028663","doi":"10.1063/1.4915146","title":"A prototype hand-held tri-modal instrument for <i>in vivo</i> ultrasound, photoacoustic, and fluorescence imaging","year":2015,"lang":"en","type":"article","venue":"Review of Scientific Instruments","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Modality (human–computer interaction); Imaging phantom; Photoacoustic imaging in biomedicine; Ultrasound; Computer science; Medical imaging; Biomedical engineering; Preclinical imaging; Ultrasound imaging; Molecular imaging; Transducer; Medical physics; Fluorescence-lifetime imaging microscopy; Computer vision; Materials science; Artificial intelligence; Optics; In vivo; Radiology; Acoustics; Medicine; Fluorescence; Physics","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":[0.001015862,0.0006723791,0.0006690564,0.0005603269,0.0004001828,0.0005994936,0.002125083,0.001341212,0.008139262],"category_scores_gemma":[0.0008034908,0.0005462575,0.0005267177,0.000337871,0.0005552645,0.0009823444,0.0006821075,0.0007121026,0.002483107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004067094,"about_ca_system_score_gemma":0.0009649501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006320541,"about_ca_topic_score_gemma":0.001074266,"domain_scores_codex":[0.9994098,0.00005114196,0.00002943116,0.0002097712,0.0002495077,0.00005043442],"domain_scores_gemma":[0.9992231,0.0001896774,0.0001174972,0.0001617959,0.0002112025,0.00009678429],"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":[0.0002410017,0.0001155057,0.0005490839,0.0003233287,0.00002780965,0.0001378917,0.00009835843,0.0004491899,0.8990759,0.0008938205,0.00253367,0.09555447],"study_design_scores_gemma":[0.0001701376,0.002849579,0.01201904,0.0001102678,0.000231496,0.005413245,0.0001297104,0.02200002,0.8507919,0.0008031772,0.1051905,0.0002909257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06704556,0.001813928,0.9113659,0.0004756221,0.0005070805,0.001507907,0.0008343469,0.009204389,0.007245166],"genre_scores_gemma":[0.1351314,0.0006908222,0.8505656,0.0004935944,0.0001052055,0.0009355894,0.000485461,0.0002000985,0.01139217],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008139262,"threshold_uncertainty_score":0.02722853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668285097538202,"score_gpt":0.2471208667677217,"score_spread":0.2304380157923397,"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."}}