{"id":"W4365514466","doi":"10.1017/s2633903x23000090","title":"Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure","year":2023,"lang":"en","type":"article","venue":"Biological Imaging","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Wellcome Trust; Ovarian Cancer Research Alliance; National Cancer Institute; Cancer Research UK; UK Research and Innovation; Memorial Sloan-Kettering Cancer Center","keywords":"Annotation; Throughput; Computer science; Computational biology; Artificial intelligence; Biology; Operating system; Wireless","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":[0.0003060303,0.0001638172,0.0002595275,0.0002022519,0.00006949263,0.0000563418,0.0001872426,0.000065683,0.000005049964],"category_scores_gemma":[0.0001486786,0.0001351244,0.00005580467,0.0005216387,0.0003632561,0.0000196492,0.0007284589,0.00007932922,2.341614e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003266493,"about_ca_system_score_gemma":0.000008596707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005247957,"about_ca_topic_score_gemma":0.000004309423,"domain_scores_codex":[0.9987994,0.00007918599,0.0002237677,0.0006117707,0.00008699096,0.0001988243],"domain_scores_gemma":[0.9992965,0.00002888812,0.0001129002,0.0004320779,0.00006760511,0.00006197635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001122115,0.000007993665,0.3887286,0.00001199593,0.0001283479,0.0000137241,0.0000246692,0.000006577591,0.5950714,0.0000435038,0.0004913742,0.01546069],"study_design_scores_gemma":[0.0004994111,0.00009236419,0.8275987,0.00002115814,0.0007023346,0.00004337429,0.000506926,0.01573056,0.1494287,0.002540638,0.00233151,0.00050437],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98687,0.003056401,0.009506441,0.0002590587,0.000007981082,0.00009819488,0.00004695613,0.00004858601,0.0001064081],"genre_scores_gemma":[0.9914159,0.002081713,0.00518504,0.0002314253,0.00002442364,0.000004848543,0.001039263,0.00001057744,0.000006820293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4456427,"threshold_uncertainty_score":0.5510215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053911184589587,"score_gpt":0.2818309682109392,"score_spread":0.2712918563650433,"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."}}