{"id":"W4302424912","doi":"10.32920/21262983","title":"Low-power noncontact photoacoustic microscope for bioimaging applications","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Microscope; Materials science; Laser; Optics; Microphone; Micrometer; Raster scan; Continuous wave; Optical power; Image resolution; Optoelectronics; Sound pressure; Acoustics","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":[0.0003562867,0.0006043533,0.0003248001,0.0004308564,0.0002244589,0.0003465982,0.0007803949,0.0006041736,0.005766498],"category_scores_gemma":[0.0004045004,0.0003491359,0.0001792293,0.0002871887,0.0002692691,0.0006929325,0.0004748086,0.0007717913,0.002477064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003556062,"about_ca_system_score_gemma":0.0003692139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004509619,"about_ca_topic_score_gemma":0.000977553,"domain_scores_codex":[0.9996183,0.00003646364,0.00001762897,0.00008796731,0.0002173499,0.00002228268],"domain_scores_gemma":[0.9997486,0.00007575643,0.00004884686,0.00003199352,0.00007066833,0.00002401919],"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":[0.000009363869,0.000008042852,0.00004259951,0.00006255772,0.000001638771,0.00002280374,0.000008695435,0.00003330816,0.9902493,0.0002243934,0.0002498815,0.009087453],"study_design_scores_gemma":[0.00001260313,0.0001205493,0.001277099,0.00001127145,0.00001253041,0.0005483142,0.00002240785,0.005418213,0.9777384,0.0002035579,0.01461956,0.00001554464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.143911,0.005766947,0.8326336,0.0005165163,0.0002638358,0.000341139,0.0004954669,0.003576125,0.01249537],"genre_scores_gemma":[0.290377,0.002924543,0.6849356,0.0003121691,0.0001235571,0.0006071297,0.000457933,0.0002289116,0.02003327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005766498,"threshold_uncertainty_score":0.01929092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008141001040022217,"score_gpt":0.2456280322229196,"score_spread":0.2374870311828974,"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."}}