{"id":"W6912383027","doi":"10.5281/zenodo.3665745","title":"CanDIG CHORD: Canadian Health Omics Repository, Distributed","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Software; Identification (biology); Software development; MEDLINE; Health data","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005798047,0.002648757,0.002029094,0.01416886,0.003738479,0.008021584,0.007397637,0.002029526,0.1168835],"category_scores_gemma":[0.02460594,0.001480178,0.001661627,0.02125304,0.00113141,0.005099223,0.006203244,0.002672569,0.08228856],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01143472,"about_ca_system_score_gemma":0.05679106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6303594,"about_ca_topic_score_gemma":0.6825556,"domain_scores_codex":[0.9974618,0.0002128243,0.0002624157,0.0004089653,0.001367004,0.0002870169],"domain_scores_gemma":[0.9835322,0.002347755,0.0005034444,0.003564003,0.007909602,0.002143088],"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":[0.0001977906,0.00001447473,0.0005918232,0.0004029052,0.00005372131,0.00008320504,0.00009673747,0.0002306211,0.0005283104,0.003109203,0.9657958,0.02889546],"study_design_scores_gemma":[0.0001834687,0.00001136062,0.002171806,0.0002752211,0.00007404537,0.0001070401,0.0001159486,0.001109462,0.0009512738,0.003806219,0.9911014,0.0000928312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001002863,0.001764698,0.02168381,0.003534041,0.0007327607,0.0004553352,0.8443059,0.09247905,0.03404148],"genre_scores_gemma":[0.006043878,0.002108476,0.04275063,0.001502651,0.000190753,0.0006385269,0.9051465,0.01718574,0.02443291],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9885653,"threshold_uncertainty_score":0.7436351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03092428332239584,"score_gpt":0.2473255774633887,"score_spread":0.2164012941409929,"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."}}