{"id":"W6967423188","doi":"10.5064/f6buax58/kzzgzk","title":"Burke_EDI_NENA.ConfirmationEDIrelate.2017.11.06.ods","year":2018,"lang":"en","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Venn diagram; Workbook; Set (abstract data type); Diagram; Microsoft excel; Table (database)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005954015,0.001404905,0.001238218,0.006972126,0.001876609,0.004506313,0.003668238,0.001436725,0.4760514],"category_scores_gemma":[0.06246936,0.001431621,0.00129961,0.01051088,0.0007463298,0.003943576,0.005255024,0.002294511,0.3462867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002488571,"about_ca_system_score_gemma":0.006538326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01967093,"about_ca_topic_score_gemma":0.03334638,"domain_scores_codex":[0.9958391,0.001088074,0.0007594933,0.0007195481,0.001115653,0.0004780706],"domain_scores_gemma":[0.9725955,0.008658513,0.001653899,0.006881954,0.009167118,0.001042959],"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":[0.00002463147,0.000012887,0.0006274485,0.0005802126,0.00001134345,0.000009900527,0.0001257931,0.00005659966,0.00002885688,0.001057875,0.9931486,0.004315717],"study_design_scores_gemma":[0.00008345533,0.000007885271,0.00258031,0.0008621238,0.00001190183,0.00002364741,0.0003503148,0.0001044366,0.0002143367,0.001688149,0.9940451,0.00002831507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001079492,0.00003025528,0.0003084988,0.000205015,0.00008345701,0.00009393667,0.993741,0.0005325009,0.00489739],"genre_scores_gemma":[0.001254428,0.0001218031,0.002901384,0.000204681,0.00003432304,0.002835129,0.9812598,0.0009717833,0.01041668],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4760514,"threshold_uncertainty_score":0.7473491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08333882415632479,"score_gpt":0.3593187148789987,"score_spread":0.2759798907226739,"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."}}