{"id":"W3046665453","doi":"10.1038/s41374-020-0475-7","title":"Characterization of pathological thyroid tissue using polarization-sensitive second harmonic generation microscopy","year":2020,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"Thyroid Cancer Diagnosis and Treatment","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Wilson Centre; Princess Margaret Cancer Centre; University of Toronto; University Health Network; Canadian Association for Girls in Science; Saint Mary's University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Government of Canada; California HIV/AIDS Research Program","keywords":"Histopathology; Pathology; Thyroid; Microscopy; Thyroid carcinoma; Chemistry; Carcinoma; Medicine; 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":[],"consensus_categories":[],"category_scores_codex":[0.00007779392,0.0001425407,0.0002422189,0.00005352202,0.00007529559,0.00002369523,0.00003195785,0.0001158645,0.00008109491],"category_scores_gemma":[0.00006904316,0.0001360132,0.00003181948,0.0004116241,0.00008751341,0.0002185668,0.00001547315,0.00009714912,0.00001579523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001018906,"about_ca_system_score_gemma":0.0002287653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008078379,"about_ca_topic_score_gemma":0.000003746776,"domain_scores_codex":[0.9990062,0.000100274,0.0003193732,0.0002779434,0.0001769506,0.0001193288],"domain_scores_gemma":[0.9991491,0.00001367779,0.0002348891,0.0001326055,0.000317518,0.0001522307],"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":[0.00003184165,0.00004725067,0.01843082,0.00005335537,0.00002749293,0.00001111175,0.0008158488,0.00001061137,0.9801537,0.0002148472,0.00007902676,0.0001241218],"study_design_scores_gemma":[0.0006939663,0.000360617,0.06169145,0.00004069313,0.00009362767,0.000004218583,0.00004259563,0.001282908,0.9353686,0.00001345453,0.0003031676,0.0001047174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954091,0.0001764749,0.00217596,0.00139295,0.0001114864,0.0004534857,0.000211148,0.00005298989,0.00001639227],"genre_scores_gemma":[0.992542,0.00003761908,0.002947353,0.003157805,0.000297617,0.00001881777,0.0009625193,0.00002181801,0.00001449242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04478509,"threshold_uncertainty_score":0.5546456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03755501469861288,"score_gpt":0.275277103273973,"score_spread":0.2377220885753601,"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."}}