{"id":"W3042460069","doi":"10.1089/bio.2020.29072.cys","title":"ISBER in the Time of COVID","year":2020,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Digital Education and Society","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"International Society for Cellular Therapy","funders":"","keywords":"Biobank; Library science; Biopreservation; Coronavirus disease 2019 (COVID-19); Political science; Computer science; Medicine; Biology; Bioinformatics","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":[0.004385765,0.0005384812,0.0006588447,0.001037421,0.004433851,0.008318016,0.00076075,0.006396586,0.06868363],"category_scores_gemma":[0.01280072,0.000310769,0.0004895703,0.0009102976,0.002653353,0.002819504,0.005205796,0.008551273,0.03180997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004686689,"about_ca_system_score_gemma":0.006900527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006516371,"about_ca_topic_score_gemma":0.01584837,"domain_scores_codex":[0.9972051,0.0003604815,0.0001133057,0.0004544154,0.001031369,0.0008353041],"domain_scores_gemma":[0.9945313,0.0005773194,0.0002450447,0.0004133203,0.001790233,0.002442807],"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":[0.0001874373,0.00003781723,0.001486992,0.0001068056,0.00001472377,0.001213644,0.0006287506,0.00006807108,0.000573836,0.05281534,0.9208456,0.02202098],"study_design_scores_gemma":[0.00000428763,0.00001193132,0.000754732,0.00006759973,0.000002246411,0.0001529697,0.000302456,0.00002119558,0.0001857404,0.001379157,0.9971119,0.000005732533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.009337174,0.0113665,0.002270141,0.4186044,0.2194677,0.00008980212,0.001605773,0.0006099385,0.3366486],"genre_scores_gemma":[0.04519804,0.002472871,0.0008955665,0.07951497,0.01365823,0.0000522714,0.0006416411,0.00040991,0.8571566],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06868363,"threshold_uncertainty_score":0.2297696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04479928049460624,"score_gpt":0.262996042288375,"score_spread":0.2181967617937688,"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."}}