{"id":"W2529141688","doi":"10.1016/j.exphem.2016.09.012","title":"Using zebrafish models of leukemia to streamline drug screening and discovery","year":2016,"lang":"en","type":"review","venue":"Experimental Hematology","topic":"Zebrafish Biomedical Research Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; Izaak Walton Killam Health Centre","funders":"","keywords":"Zebrafish; Drug discovery; Leukemia; Drug; Computational biology; Computer science; Medicine; Pharmacology; Bioinformatics; Biology; Internal medicine; Genetics","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":[0.0006916022,0.0009551061,0.001008512,0.001812681,0.0002033545,0.0008727774,0.0007473297,0.0008062464,0.002065479],"category_scores_gemma":[0.0005318784,0.0002787577,0.0005000834,0.001188155,0.0005733086,0.0008927257,0.0005788521,0.001972663,0.0009909275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008052959,"about_ca_system_score_gemma":0.00118573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001954258,"about_ca_topic_score_gemma":0.006502363,"domain_scores_codex":[0.9998565,0.0000160127,0.00001695327,0.00002189825,0.00007115837,0.00001750703],"domain_scores_gemma":[0.9998011,0.0000729159,0.0000342737,0.000007694182,0.00006164449,0.00002241554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000107245,0.00008419971,0.0003007929,0.01133954,0.00009482985,0.0003566665,0.00005139594,0.0006445816,0.02005089,0.008959975,0.03704468,0.9209652],"study_design_scores_gemma":[0.00003116635,0.0001143479,0.000649874,0.001508016,0.000159993,0.000807978,0.00003379642,0.0001537213,0.005023099,0.002116343,0.9893727,0.000028977],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003564051,0.9950794,0.001277179,0.0006144348,0.0002554134,0.00001575939,0.00008736068,0.00003450873,0.002279449],"genre_scores_gemma":[0.001550196,0.9956917,0.0009522431,0.0002918378,0.00008044583,0.00001621577,0.00008965826,0.000004192349,0.00132351],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002065479,"threshold_uncertainty_score":0.006909728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05692779520633688,"score_gpt":0.3945645034787561,"score_spread":0.3376367082724192,"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."}}