{"id":"W3082468582","doi":"10.1016/j.infpip.2020.100087","title":"Corrigendum to “Detecting Clostridioides (Clostridium) difficile using canine teams: What does the nose know?” [Infect Prev Pract 1 (2019) 100005]","year":2020,"lang":"en","type":"erratum","venue":"Infection Prevention in Practice","topic":"Clostridium difficile and Clostridium perfringens research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Vancouver Coastal Health","funders":"","keywords":"Clostridioides; Clostridium difficile; Nose; Clostridium; Microbiology; Computer science; Biology; Medicine; Surgery; Bacteria","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":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.003338764,0.001398236,0.001769481,0.001397463,0.0009117789,0.001251334,0.0006528961,0.001540672,0.001403518],"category_scores_gemma":[0.01316047,0.001090591,0.0009535075,0.003743687,0.0002263758,0.002435512,0.0008255389,0.007469159,0.0008070383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003456241,"about_ca_system_score_gemma":0.004063083,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008209336,"about_ca_topic_score_gemma":0.001942072,"domain_scores_codex":[0.9892377,0.002178557,0.002398331,0.002181724,0.002381927,0.001621793],"domain_scores_gemma":[0.992815,0.001536019,0.001540119,0.001834056,0.001453204,0.0008216175],"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":[0.004565276,0.004358803,0.001164024,0.002502103,0.002404633,0.0008568579,0.001839762,0.000944059,0.05433838,0.0001003422,0.8301573,0.09676842],"study_design_scores_gemma":[0.002476577,0.002185971,0.0005113892,0.004843838,0.002223668,0.001330914,0.002875732,0.001188572,0.03783057,0.00003259847,0.9431909,0.001309234],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4660447,0.03955223,0.004178267,0.06733259,0.3007394,0.03929424,0.0007793127,0.00320701,0.07887226],"genre_scores_gemma":[0.3914922,0.1353224,0.001867371,0.006705933,0.03655735,0.003098111,0.003958989,0.002071174,0.4189265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3400542,"threshold_uncertainty_score":0.999971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03974853006038025,"score_gpt":0.3606404920913357,"score_spread":0.3208919620309554,"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."}}