{"id":"W3005819879","doi":"10.3390/s20041027","title":"Rapid High-Resolution Mosaic Acquisition for Photoacoustic Remote Sensing","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Centre for Bioengineering and Biotechnology, University of Waterloo; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Mitacs; illumiSonics","keywords":"Raster scan; Optics; Field of view; Resolution (logic); Image resolution; Materials science; Frame rate; Photoacoustic imaging in biomedicine; Computer science; Computer vision; Biomedical engineering; Artificial intelligence; Physics; Engineering","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":[0.0003413792,0.0003032277,0.0002013239,0.0004835971,0.0002095911,0.0002487981,0.0003343525,0.0003196537,0.002518554],"category_scores_gemma":[0.0004514389,0.0002725662,0.0001834474,0.0003383216,0.0002181254,0.0004017366,0.0004319227,0.0004179779,0.0005269123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002969792,"about_ca_system_score_gemma":0.0004037982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000794498,"about_ca_topic_score_gemma":0.00219619,"domain_scores_codex":[0.999843,0.00001845436,0.000006878287,0.0000400212,0.00007477815,0.00001686141],"domain_scores_gemma":[0.9997949,0.00005372061,0.00003541314,0.00004790374,0.0000489044,0.00001922377],"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":[0.00002874556,0.00001387032,0.0002237007,0.00003713699,0.00000425411,0.00002965977,0.00002529424,0.0002993078,0.9840725,0.0004506011,0.0002514873,0.01456349],"study_design_scores_gemma":[0.00002079528,0.0002168082,0.006599248,0.00002150507,0.00001513652,0.0007856579,0.00005322185,0.04008206,0.9421245,0.000844624,0.009198522,0.00003785501],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3029118,0.001457759,0.6866749,0.0001988096,0.00008821233,0.000377381,0.0004803798,0.002244543,0.00556629],"genre_scores_gemma":[0.3677497,0.0005502911,0.6289904,0.0000608205,0.00002405068,0.0002819902,0.0004247728,0.000169638,0.00174825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002518554,"threshold_uncertainty_score":0.008425415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378173360466984,"score_gpt":0.2075306465857883,"score_spread":0.1937489129811185,"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."}}