{"id":"W2949261725","doi":"10.1089/bio.2019.0039","title":"The Importance of Human Tissue Bioresources in Advancing Biomedical Research","year":2019,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"HER2/EGFR in Cancer Research","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute","keywords":"Personalized medicine; Precision medicine; Medicine; Biotechnology; Business; Computational biology; Bioinformatics; Pathology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.002723284,0.00008195604,0.0001855553,0.0002820673,0.0001573471,0.00004010977,0.0001975082,0.0001019769,0.0001719437],"category_scores_gemma":[0.0004258204,0.00005515817,0.00002368866,0.0007445011,0.0003296521,0.00007859446,0.0001769941,0.0003460138,0.00001480365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009303779,"about_ca_system_score_gemma":0.0001081337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004705866,"about_ca_topic_score_gemma":0.0003810058,"domain_scores_codex":[0.9980655,0.0001146627,0.0003682438,0.000259895,0.0008040983,0.0003876554],"domain_scores_gemma":[0.9990151,0.0002557749,0.00007432191,0.0003507287,0.0002131432,0.00009090975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006379726,0.00004042568,0.751776,0.0001794255,0.000006889942,0.000007694719,0.0002831682,2.731733e-7,0.237351,0.001295837,0.000754041,0.008241436],"study_design_scores_gemma":[0.001662233,0.0008676565,0.787383,0.0008595317,0.000006656027,0.00001286694,0.001782962,0.0008281062,0.04528634,0.00157408,0.1595737,0.0001628415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915625,0.001349359,0.000005248947,0.004671244,0.00006150756,0.0005162712,0.000002762467,0.00001710397,0.00181398],"genre_scores_gemma":[0.9984842,0.000272883,0.0001847575,0.00009659963,0.0001047464,0.00002010806,0.00001327215,0.00001314715,0.000810314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1920647,"threshold_uncertainty_score":0.2249285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08483540331221695,"score_gpt":0.4416111439184968,"score_spread":0.3567757406062799,"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."}}