{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002181376,0.000432861,0.0007142096,0.0006562748,0.0002953073,0.00009738894,0.0007602811,0.0003911115,0.0007329321],"category_scores_gemma":[0.001647539,0.000473813,0.0002090959,0.0005427203,0.0002919542,0.00008851775,0.001787139,0.00396664,0.00002024158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001458356,"about_ca_system_score_gemma":0.0004010453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004216084,"about_ca_topic_score_gemma":0.00001006137,"domain_scores_codex":[0.9952855,0.0004509566,0.0006730913,0.0007111636,0.001749384,0.001129872],"domain_scores_gemma":[0.997056,0.001016863,0.0001304102,0.001211099,0.0003595311,0.0002260729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002683915,0.0001628261,0.00006656035,0.004424264,0.0004177242,0.0008571091,0.003569787,0.8236057,0.09421938,0.0003682649,0.007395034,0.06464501],"study_design_scores_gemma":[0.0007674553,0.0002335078,0.0003291919,0.0008078628,0.00006684076,0.00007957029,0.003197384,0.9897651,0.001398472,0.001950009,0.0008298703,0.0005747145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8529195,0.002316935,0.130956,0.0001223531,0.001606001,0.00139602,0.0007847006,0.0008492258,0.009049325],"genre_scores_gemma":[0.9925748,0.0002815141,0.006034909,0.00001283909,0.0002462381,0.00001885004,0.0002136676,0.0001292085,0.000487956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1661595,"threshold_uncertainty_score":0.9997714,"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."}}