{"id":"W1981874274","doi":"10.1038/ejhg.2014.272","title":"The EuroBioBank Network: 10 years of hands-on experience of collaborative, transnational biobanking for rare diseases","year":2014,"lang":"en","type":"article","venue":"European Journal of Human Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"Medical Research Council; European Organisation for Rare Diseases; Fondazione Telethon","keywords":"Biobank; European commission; Biorepository; Best practice; Collaborative network; Business; Political science; Knowledge management; Computer science; Biology; Bioinformatics; European union","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":[0.0002568412,0.00009488033,0.0001370508,0.00003127736,0.0001196808,0.00002274995,0.0003249718,0.00001891277,0.000008984367],"category_scores_gemma":[0.00007969388,0.00007481993,0.000141834,0.00005980059,0.000161105,0.000002461815,0.00003898031,0.0000393369,3.316979e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003780862,"about_ca_system_score_gemma":0.00005822157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.879007e-8,"about_ca_topic_score_gemma":0.000001149369,"domain_scores_codex":[0.9990479,0.000163553,0.0003955898,0.0001134029,0.0001475899,0.0001320117],"domain_scores_gemma":[0.9989207,0.00004951705,0.0004034871,0.000182001,0.0003822836,0.00006194862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004233605,0.001047892,0.01262852,0.0002875948,0.0009181898,0.00005462328,0.002596674,0.0574524,0.8127294,0.01401475,0.03799067,0.05604574],"study_design_scores_gemma":[0.01184742,0.02190663,0.2001573,0.0002946149,0.0004435905,0.00005793007,0.001139519,0.0004223449,0.2678722,0.001688804,0.4931678,0.001001774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970377,0.001661863,0.0007028411,0.00004088592,0.0001280641,0.00009400722,0.0000616154,0.000001281484,0.0002717534],"genre_scores_gemma":[0.9987502,0.0002643865,0.0004890126,0.00004474415,0.0003194357,0.000001192135,0.00002559232,0.00002184723,0.00008355497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5448571,"threshold_uncertainty_score":0.3051068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01140608125096452,"score_gpt":0.2505513774312038,"score_spread":0.2391452961802393,"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."}}