{"id":"W4239980103","doi":"10.21203/rs.3.rs-35143/v1","title":"Biobanking Framework: “One Size Fits All”","year":2020,"lang":"en","type":"preprint","venue":"Research Square (Research Square)","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Biobank; Computer science; Data science; Biology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.04525759,0.001777003,0.002163401,0.003551227,0.00313645,0.01625069,0.007970119,0.005273892,0.01946347],"category_scores_gemma":[0.02964051,0.00210305,0.004005068,0.002957595,0.00398009,0.01539814,0.02146642,0.006426352,0.0164127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003982775,"about_ca_system_score_gemma":0.01111833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006338696,"about_ca_topic_score_gemma":0.004370886,"domain_scores_codex":[0.9738056,0.01100771,0.0038865,0.003959622,0.00499219,0.002348383],"domain_scores_gemma":[0.9776922,0.006427789,0.001508995,0.007260444,0.003526038,0.003584623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009852995,0.0006026531,0.003795657,0.002740634,0.0003709363,0.001385961,0.004342934,0.01462777,0.008385351,0.6131027,0.2015458,0.1481143],"study_design_scores_gemma":[0.0001940828,0.0001677671,0.001083484,0.001979524,0.0001322465,0.0007435954,0.0007697857,0.04444771,0.005881639,0.2043702,0.7399591,0.0002708886],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002372441,0.0009370978,0.9111507,0.00739284,0.0005232941,0.002680319,0.002805408,0.05456935,0.01756855],"genre_scores_gemma":[0.04345404,0.00127542,0.9148857,0.00477269,0.0004105775,0.003415754,0.01227809,0.008355692,0.01115207],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04525759,"threshold_uncertainty_score":0.2393478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7811502287770828,"score_gpt":0.5918697447640784,"score_spread":0.1892804840130045,"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."}}