{"id":"W2017067437","doi":"10.1002/cyto.a.22212","title":"ICEFormat—the image cytometry experiment format","year":2012,"lang":"en","type":"letter","venue":"Cytometry Part A","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Computer science; DICOM; Image file formats; File format; Software; Metadata; Standardization; Interoperability; Digital image; Digital imaging; Cytometry; Data file; Image processing; Image (mathematics); Database; World Wide Web; Artificial intelligence; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005091495,0.001484761,0.001668361,0.003667346,0.001358471,0.003952266,0.005575318,0.00275101,0.1247543],"category_scores_gemma":[0.009657091,0.0009813556,0.0009861342,0.002964992,0.0008281443,0.004150349,0.003070889,0.002706169,0.1390419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001956796,"about_ca_system_score_gemma":0.002835951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002304214,"about_ca_topic_score_gemma":0.002467321,"domain_scores_codex":[0.9970439,0.0004162796,0.0004188917,0.000512448,0.001296484,0.0003119991],"domain_scores_gemma":[0.9926667,0.001280957,0.0004182683,0.002054866,0.003173214,0.0004060302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008670606,0.00008669072,0.0007790031,0.000749325,0.00003616931,0.0001724715,0.00009737108,0.0006995377,0.02337502,0.01004282,0.8831276,0.07996687],"study_design_scores_gemma":[0.00009193877,0.00007080222,0.001010223,0.0001407247,0.00002109246,0.0003034568,0.00003554009,0.002377953,0.02951142,0.003755894,0.9626018,0.00007901278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005869674,0.002959793,0.3054919,0.002876702,0.004390191,0.003419598,0.3353438,0.2147846,0.1248637],"genre_scores_gemma":[0.02737818,0.002865551,0.2109115,0.006050381,0.001001804,0.006875781,0.6421117,0.03166046,0.07114467],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1247543,"threshold_uncertainty_score":0.4173447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127974244326854,"score_gpt":0.2803720256577992,"score_spread":0.2675746012251138,"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."}}