{"id":"W4221165690","doi":"10.1364/ol.457142","title":"Time-domain feature extraction for target specificity in photoacoustic remote sensing microscopy","year":2022,"lang":"en","type":"article","venue":"Optics Letters","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Illumisonics (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Frontiers Foundation; Mitacs; University of Waterloo; Canada Foundation for Innovation; illumiSonics","keywords":"Photoacoustic imaging in biomedicine; Biomolecule; Absorption (acoustics); Microscopy; Computer science; Materials science; Nanosecond; Time domain; Artificial intelligence; Computer vision; Nanotechnology; Optics; Laser; Physics","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":[0.0004515624,0.0006255631,0.0005366344,0.001284676,0.0002972219,0.0006649157,0.000671956,0.0006788698,0.001450601],"category_scores_gemma":[0.001442812,0.0002428896,0.0006178466,0.001173422,0.0003377599,0.0006430693,0.0005557723,0.0007367142,0.001004141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000408334,"about_ca_system_score_gemma":0.0004724172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000911977,"about_ca_topic_score_gemma":0.001231398,"domain_scores_codex":[0.9997284,0.00003823448,0.00001817102,0.00008627529,0.00008429062,0.00004466901],"domain_scores_gemma":[0.9995351,0.0001643326,0.00007419827,0.00006477443,0.0001403702,0.00002127337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003043983,0.000146964,0.001129998,0.0002268968,0.00005282411,0.0001382147,0.0001275203,0.03280336,0.4645488,0.003694155,0.002787713,0.494039],"study_design_scores_gemma":[0.00001686669,0.0001151954,0.004114863,0.00002000856,0.00004303773,0.0003142334,0.00007914301,0.7979655,0.1870767,0.004623862,0.005588413,0.00004212673],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03670524,0.0002742078,0.960257,0.0001076641,0.00003329089,0.0000516556,0.0001976846,0.001481016,0.0008922926],"genre_scores_gemma":[0.3426456,0.000503669,0.6536608,0.00009647662,0.00005107126,0.0002081897,0.0008519983,0.0002656387,0.001716456],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001450601,"threshold_uncertainty_score":0.004852712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005829544059153113,"score_gpt":0.2169404941168356,"score_spread":0.2111109500576824,"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."}}