{"id":"W3044946220","doi":"10.1364/ol.397614","title":"Label-free lipid contrast imaging using non-contact near-infrared photoacoustic remote sensing microscopy","year":2020,"lang":"en","type":"article","venue":"Optics Letters","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Materials science; Optics; Microscopy; Absorption (acoustics); Raman scattering; Near-infrared spectroscopy; Microscope; Raman spectroscopy; Optoelectronics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001414682,0.0004400808,0.0004537317,0.00007765975,0.0002351358,0.0003344324,0.0003636965,0.00008116865,0.00002536522],"category_scores_gemma":[0.0001688783,0.0005168857,0.0001148552,0.0003056574,0.0001105107,0.0002658072,0.00009600867,0.0005663109,0.00003492454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208778,"about_ca_system_score_gemma":0.00006769738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007671776,"about_ca_topic_score_gemma":0.000001495971,"domain_scores_codex":[0.9979593,0.00002760184,0.0004412023,0.000425827,0.0002826545,0.0008634095],"domain_scores_gemma":[0.9989224,0.0001489353,0.00008692182,0.000487801,0.00006013659,0.0002937815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002141316,0.00000550394,0.0000511555,0.0001390551,0.00007827748,0.0002154912,0.0007526371,0.0369622,0.9564657,0.000001577489,0.003978854,0.001328101],"study_design_scores_gemma":[0.001345245,0.0000132974,0.00004574265,0.0001839717,0.0001437732,0.00009506836,0.0001773074,0.9426378,0.05428335,0.00001147618,0.0005164808,0.0005464752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3311932,0.0001135457,0.66514,0.001065598,0.0008440512,0.0002646956,0.00005394519,0.0003758031,0.0009492186],"genre_scores_gemma":[0.7883555,0.00002305234,0.2030343,0.007804587,0.0005684479,7.638524e-7,0.00001837285,0.0001811775,0.00001380007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9056756,"threshold_uncertainty_score":0.9997283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009809628487867,"score_gpt":0.2163814736516014,"score_spread":0.2062833773667227,"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."}}