{"id":"W4312314815","doi":"10.1109/pn56061.2022.9908334","title":"Probing Micron-sized Objects with Photoacoustic Sensing: Theory and Applications","year":2022,"lang":"en","type":"article","venue":"2022 Photonics North (PN)","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Aerosolization; Coronavirus disease 2019 (COVID-19); Photoacoustic spectroscopy; Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Photoacoustic imaging in biomedicine; 2019-20 coronavirus outbreak; Transmission (telecommunications); Coronavirus; Respiratory system; Virology; Medicine; Materials science; Nanotechnology; Intensive care medicine; Computer science; Optics; Physics; Infectious disease (medical specialty); Pathology; Internal medicine; Disease; Inhalation; Outbreak; Anesthesia","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":[0.0003815131,0.0005079166,0.0003723832,0.0005429887,0.000309579,0.0009559874,0.0008615153,0.00169037,0.001400277],"category_scores_gemma":[0.0006102349,0.0003969661,0.0003891792,0.000450389,0.001543207,0.001561974,0.0008708888,0.001049715,0.0006016475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004828198,"about_ca_system_score_gemma":0.0002689576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003064151,"about_ca_topic_score_gemma":0.0002590725,"domain_scores_codex":[0.999686,0.00004396992,0.00001249005,0.00008222547,0.0001482486,0.00002709379],"domain_scores_gemma":[0.9995617,0.0002826307,0.00004885086,0.00003369487,0.00005576082,0.00001732719],"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":[0.00009973822,0.000235672,0.001919391,0.00182587,0.00006488814,0.0007240094,0.0006066277,0.03216457,0.6615219,0.1719909,0.003342392,0.125504],"study_design_scores_gemma":[0.00004163033,0.0005527854,0.001668167,0.0002772487,0.00004653146,0.001739229,0.0003634758,0.6459115,0.1766609,0.1288722,0.04366255,0.000203739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04894311,0.03732499,0.8742136,0.003451381,0.0008812326,0.0001384862,0.0001397061,0.0004400863,0.03446726],"genre_scores_gemma":[0.6949371,0.02793065,0.2645113,0.001497833,0.0008303749,0.0003802237,0.0001133896,0.00006474739,0.009734498],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00169037,"threshold_uncertainty_score":0.004684329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008068373041217825,"score_gpt":0.2068296031369664,"score_spread":0.1987612300957486,"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."}}