{"id":"W4230281167","doi":"10.1089/bio.2017.29021.abstracts","title":"The International Society for Biological and Environmental Repositories Presents Abstracts from Its Annual Meeting Due North: Aligning Biobanking Practice with Evolving Evidence and Innovation May 9–12, 2017 Toronto, Canada","year":2017,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Biobank; Political science; Business; Library science; Geography; Biology; Bioinformatics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006118602,0.0001459713,0.000154343,0.00002475504,0.001419133,0.0003271422,0.0001547276,0.0001014493,0.000001693377],"category_scores_gemma":[0.003291128,0.0000974887,0.00001789695,0.00003957273,0.0002071939,0.001126446,0.0002330768,0.000136287,7.608163e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149182,"about_ca_system_score_gemma":0.0001171024,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04321512,"about_ca_topic_score_gemma":0.02688333,"domain_scores_codex":[0.9987347,0.00001670873,0.0003128774,0.0004253484,0.0002984203,0.0002119483],"domain_scores_gemma":[0.9984535,0.0004474414,0.0005538288,0.0002614301,0.0002366461,0.00004716841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004207919,0.00002828255,0.9647446,0.00006590888,0.000143792,0.00001310077,0.000663757,0.000001400374,0.02132433,0.0002809289,0.0009187767,0.01139431],"study_design_scores_gemma":[0.000561183,0.0001408293,0.9742578,0.0003067636,0.00004603661,0.00005186665,0.00335587,0.0006432729,0.006096672,0.00007468014,0.01431611,0.0001489268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867896,0.004054478,0.00005130593,0.008056174,0.0002456545,0.0005081551,0.00004055997,0.00002731973,0.0002266849],"genre_scores_gemma":[0.9937041,0.001891005,0.003678766,0.0002161994,0.0003242028,0.00003385967,0.00006691064,0.000008248151,0.00007669749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01633179,"threshold_uncertainty_score":0.9998809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06805958291763853,"score_gpt":0.320096911103722,"score_spread":0.2520373281860834,"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."}}