{"id":"W3196668880","doi":"10.1089/bio.2017.29024.apj","title":"The 2017 ISBER Annual Meeting & Exhibits: “Due North: Aligning Biobanking Practice with Evolving Evidence and Innovation”","year":2017,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Biobank; PARRY; Library science; Biopreservation; Biology; Bioinformatics; Computer science","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007487414,0.0002134082,0.0002601584,0.0001907032,0.003006269,0.001171168,0.0004108071,0.0002441728,0.00001276311],"category_scores_gemma":[0.07387462,0.000141507,0.00003201108,0.0004500857,0.0007246737,0.001758385,0.0006518696,0.001055063,0.000008336168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006343246,"about_ca_system_score_gemma":0.0002604523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006882208,"about_ca_topic_score_gemma":0.001864901,"domain_scores_codex":[0.997111,0.000141784,0.000600003,0.0005812654,0.001130162,0.0004357379],"domain_scores_gemma":[0.9880904,0.007265953,0.0008050408,0.0009907878,0.002718816,0.0001290342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006284476,0.0000793141,0.9480083,0.0004618002,0.0001641248,0.00006462228,0.00231853,0.000004232321,0.008115734,0.01904509,0.00150444,0.01960537],"study_design_scores_gemma":[0.001869115,0.0004432699,0.9158815,0.007013572,0.0001958269,0.0002639736,0.00240848,0.001405753,0.001647583,0.004008803,0.06425549,0.0006065975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438021,0.002565432,0.0006417705,0.04616104,0.0001785789,0.0006301488,0.000007933119,0.00008267917,0.005930339],"genre_scores_gemma":[0.9851457,0.00241691,0.009244855,0.001354683,0.0003983395,0.00002605847,0.00001380372,0.00002853344,0.001371086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0663872,"threshold_uncertainty_score":0.9998657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4183698858563308,"score_gpt":0.517933484279775,"score_spread":0.0995635984234442,"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."}}