{"id":"W2327569758","doi":"10.1136/jclinpath-2012-200974","title":"Validation of tissue microarrays in oral epithelial dysplasia using a novel virtual-array technique","year":2012,"lang":"en","type":"article","venue":"Journal of Clinical Pathology","topic":"HER2/EGFR in Cancer Research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Cancer Research UK","keywords":"Tissue microarray; Immunohistochemistry; Virtual microscopy; Pathology; Reliability (semiconductor); Computer science; Intraclass correlation; Dysplasia; Oral mucosa; Medicine; Reproducibility; Computational biology; Pattern recognition (psychology); Artificial intelligence; Biology; Mathematics; Statistics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.008389018,0.0001309575,0.0009950043,0.0003681299,0.00002003914,0.000005155994,0.0001923406,0.0004493755,0.0002239841],"category_scores_gemma":[0.004028537,0.0001053448,0.0002035745,0.0002786813,0.0003090037,0.0001512943,0.00005490164,0.001243904,0.00001893943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009792018,"about_ca_system_score_gemma":0.0005631888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002205174,"about_ca_topic_score_gemma":0.000004507847,"domain_scores_codex":[0.9963702,0.0006070337,0.002050699,0.0001629939,0.0004277398,0.000381342],"domain_scores_gemma":[0.9975883,0.0006492341,0.0008630269,0.0002541945,0.0003729885,0.0002722342],"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":[0.0008481675,0.0008343374,0.1215446,0.00005337326,0.0000291127,0.0001409392,0.0002077109,0.00001788871,0.8708601,0.000071068,0.0001096492,0.005283031],"study_design_scores_gemma":[0.007477746,0.005908818,0.1420512,0.0006966341,0.0001904181,0.006936059,0.0001922887,0.0000357975,0.8241386,0.0003089008,0.011828,0.0002355274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973375,0.000153142,0.02396507,0.0007012062,0.0009656615,0.0003383359,0.0000104396,0.000006306505,0.0004848488],"genre_scores_gemma":[0.9455586,0.0000875597,0.05305574,0.0002167534,0.0009979588,0.000004684386,0.000002021495,0.00002557613,0.00005111114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0467215,"threshold_uncertainty_score":0.5404214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1688893957721167,"score_gpt":0.4997639523913587,"score_spread":0.330874556619242,"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."}}