{"id":"W6931381173","doi":"10.5281/zenodo.4299750","title":"euCanSHare. Deliverable 1.3 - Comparative cross-mapping table detailing which participating cohorts are compliant with euCanSHare requirements","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"European Commission","keywords":"Deliverable; Interoperability; Table (database); Principal (computer security); Corporate governance; Representation (politics); Data collection; Best practice","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02333253,0.001230851,0.001561505,0.004460293,0.001482709,0.004311037,0.002882045,0.001683913,0.4152524],"category_scores_gemma":[0.07304272,0.001459364,0.001427794,0.004065067,0.0008999916,0.002774429,0.005099463,0.001667808,0.2008171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002368755,"about_ca_system_score_gemma":0.007945647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007505514,"about_ca_topic_score_gemma":0.01164953,"domain_scores_codex":[0.9897528,0.003387416,0.001632385,0.001577656,0.002999461,0.0006503621],"domain_scores_gemma":[0.9456317,0.02916813,0.003527035,0.01187881,0.00793278,0.001861516],"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":[0.0008603565,0.000109189,0.002676793,0.002735655,0.00008916459,0.0002600507,0.000788268,0.000686271,0.003358648,0.009874488,0.9203168,0.05824433],"study_design_scores_gemma":[0.0002858573,0.0001232618,0.008958716,0.0008881151,0.0000631504,0.00036559,0.0004715033,0.0003884129,0.0042546,0.01259169,0.9714904,0.000118676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003486577,0.0003237248,0.05293432,0.001249784,0.0005060775,0.002406334,0.8808604,0.02020453,0.03802818],"genre_scores_gemma":[0.01278909,0.0003722361,0.08119655,0.001477514,0.000185682,0.009650421,0.8430806,0.01517025,0.03607772],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4152524,"threshold_uncertainty_score":0.8340714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3757121057846883,"score_gpt":0.4009559652018224,"score_spread":0.02524385941713408,"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."}}