{"id":"W3124767363","doi":"10.3389/fphy.2020.616618","title":"Dual-Modal Photoacoustic Imaging and Optical Coherence Tomography [Review]","year":2021,"lang":"en","type":"article","venue":"Frontiers in Physics","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Optical coherence tomography; Photoacoustic imaging in biomedicine; Molecular imaging; Computer science; Optics; Biomedical engineering; Tomography; Medical imaging; Modalities; Optical imaging; Medical physics; Materials science; Artificial intelligence; Medicine; Physics; In vivo","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":[0.0000940789,0.0001855024,0.0003018792,0.00004413967,0.00004132602,0.00003945993,0.00008298315,0.00003375932,0.00001462243],"category_scores_gemma":[0.00003965127,0.0002082498,0.0000603937,0.0003886276,0.00009982806,0.0001605035,0.0000387697,0.0002828702,0.000003185446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005465423,"about_ca_system_score_gemma":0.00004055417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004073538,"about_ca_topic_score_gemma":8.389562e-7,"domain_scores_codex":[0.9990115,0.00001905547,0.0002021659,0.0002483256,0.0001583285,0.0003606215],"domain_scores_gemma":[0.99959,0.00004978784,0.00001962442,0.0002130883,0.00003823704,0.00008931154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000319611,0.0004925279,0.09978607,0.008690128,0.0005300645,0.001885896,0.001925625,0.02699282,0.08294224,0.001537161,0.2150662,0.5601193],"study_design_scores_gemma":[0.001511219,0.0000197174,0.006330426,0.002776221,0.0003164234,0.0002181869,0.001225364,0.946997,0.02351406,0.01111427,0.004595208,0.001381912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04713768,0.1124325,0.8169574,0.0002177698,0.003295247,0.000513303,0.00006979318,0.0004774864,0.01889889],"genre_scores_gemma":[0.9705935,0.004690301,0.02390605,0.0004658139,0.0001849832,0.00003778332,0.00002411689,0.00004921013,0.00004827388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9234558,"threshold_uncertainty_score":0.8492181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004785531736359717,"score_gpt":0.20272887202043,"score_spread":0.1979433402840703,"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."}}