{"id":"W4224126815","doi":"10.21203/rs.3.rs-1498285/v1","title":"Virtual Histological Staining of Label-Free Total Absorption Photoacoustic Remote Sensing (TA-PARS)","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Illumisonics (Canada); University of Alberta; University of Waterloo","funders":"Centre for Bioengineering and Biotechnology, University of Waterloo; University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Staining; Histology; Concordance; Gold standard (test); Histopathology; Pathology; Biomedical engineering; Digital pathology; Absorption (acoustics); Computer science; Medicine; Materials science; Radiology; Internal medicine","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":[0.0005170866,0.0004023176,0.000151806,0.0003436736,0.00009685553,0.0004613679,0.0004417904,0.0004444545,0.001836507],"category_scores_gemma":[0.0006962956,0.0002211006,0.0003956551,0.0001426335,0.000534392,0.0003865621,0.0005502321,0.0004559361,0.0005140827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000272111,"about_ca_system_score_gemma":0.0002793137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003973727,"about_ca_topic_score_gemma":0.0006051504,"domain_scores_codex":[0.9997849,0.00004546294,0.000007435698,0.00005401814,0.0000833003,0.00002491121],"domain_scores_gemma":[0.9997131,0.00009571733,0.00005190678,0.00006233544,0.00005474591,0.00002216534],"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":[0.0002586086,0.00008516166,0.00246429,0.0002348895,0.00007490246,0.0005982117,0.0001348763,0.3280793,0.5743794,0.00648643,0.00215195,0.08505197],"study_design_scores_gemma":[0.00001141283,0.0001738294,0.002506402,0.00002080281,0.00002603957,0.0005752483,0.00004377621,0.7951472,0.1948326,0.003015622,0.003614525,0.00003258115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1939646,0.0002328076,0.7984741,0.0002503683,0.00009794468,0.0000628205,0.0002082659,0.002121314,0.004587794],"genre_scores_gemma":[0.7827106,0.0002621258,0.2117592,0.0001739834,0.00002383342,0.0000689464,0.0002908821,0.0002220004,0.004488511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001836507,"threshold_uncertainty_score":0.006143749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04925256439015541,"score_gpt":0.3300112198385369,"score_spread":0.2807586554483815,"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."}}