{"id":"W2028089161","doi":"10.1126/science.316.5826.830","title":"Biobanking Primer: Down to Basics","year":2007,"lang":"en","type":"letter","venue":"Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Biobank; Primer (cosmetics); Computational biology; Computer science; Biology; Bioinformatics; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01060428,0.0007041077,0.0008407331,0.001160338,0.002891604,0.004593578,0.001871241,0.01842432,0.1179931],"category_scores_gemma":[0.02980709,0.0009151546,0.0008532628,0.0009743863,0.001809567,0.005386941,0.003841631,0.02246738,0.1398754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002457404,"about_ca_system_score_gemma":0.00939598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003736845,"about_ca_topic_score_gemma":0.005331505,"domain_scores_codex":[0.9933921,0.002568502,0.0009713118,0.000498765,0.001815324,0.0007541308],"domain_scores_gemma":[0.9795321,0.01028747,0.0007225719,0.001025901,0.006471413,0.001960638],"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":[0.00001787343,0.00001732105,0.00005756496,0.00006007689,9.614048e-7,0.00009488776,0.0001252423,0.00001122283,0.000213124,0.003284235,0.9878951,0.008222344],"study_design_scores_gemma":[0.00001354274,0.00001548385,0.0001645254,0.0001993957,0.000001363669,0.0001515287,0.0001205513,0.00002376573,0.00008869401,0.002330042,0.996882,0.000009293834],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0006452393,0.003183767,0.007589201,0.8063916,0.05589795,0.0009758123,0.003442609,0.001543368,0.1203304],"genre_scores_gemma":[0.002392143,0.002229854,0.009759239,0.7745021,0.009209489,0.001438131,0.002214635,0.000802382,0.197452],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1179931,"threshold_uncertainty_score":0.3947263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5137747965766837,"score_gpt":0.6138421988738699,"score_spread":0.1000674022971862,"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."}}