{"id":"W4302018627","doi":"10.5281/zenodo.7148861","title":"EOSC-Life Public database inventorying the national health databases and registries and describing their access procedures for reuse for research purposes","year":2022,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Information Technology Association of Canada","funders":"Horizon 2020 Framework Programme","keywords":"Database; Reuse; Computer science; Public access; World Wide Web; Engineering","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01370933,0.000303549,0.0003202928,0.0003491667,0.01020009,0.001573516,0.001895601,0.00007923495,0.002648416],"category_scores_gemma":[0.03258744,0.0002706014,0.00005633369,0.0006398477,0.001047122,0.001056393,0.009264179,0.0008259564,0.00006218963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001481828,"about_ca_system_score_gemma":0.0002492009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004712293,"about_ca_topic_score_gemma":0.00005454677,"domain_scores_codex":[0.9942208,0.001199505,0.000560389,0.001333413,0.001771395,0.0009144965],"domain_scores_gemma":[0.9970388,0.0007372808,0.0004637351,0.0008306445,0.0004713707,0.0004581451],"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":[0.000115235,0.0001595807,0.0002905365,0.001249191,0.00007999306,0.000003739053,0.001851967,0.00002698715,0.0003655677,0.0007553077,0.9412711,0.05383075],"study_design_scores_gemma":[0.000435692,0.0002104632,0.001143184,0.0001673633,0.00001453419,0.00009659542,0.001734626,0.0002430777,0.00005178622,0.0003519494,0.9952852,0.0002655937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1980079,0.03110154,0.05325783,0.2093754,0.002425374,0.09949384,0.1501544,0.004794248,0.2513895],"genre_scores_gemma":[0.7810741,0.07587618,0.007349029,0.009836016,0.003031943,0.0001510778,0.1007362,0.01193374,0.01001175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5830661,"threshold_uncertainty_score":0.9999746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4558473501788927,"score_gpt":0.3975960294570524,"score_spread":0.05825132072184025,"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."}}