{"id":"W6977503401","doi":"10.7298/9c4y-v945","title":"Surveillance Optimization Project for Chronic Wasting Disease dataset for Ontario, Canada, 2017-2020","year":2023,"lang":"en","type":"dataset","venue":"eCommons (Cornell University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Christian ministry; Chronic wasting disease; Wildlife; General partnership; Natural resource; Wasting; Disease surveillance; Public health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004942783,0.0008296318,0.0008640151,0.0008862558,0.0007823789,0.000136693,0.001857078,0.0003195475,0.0001654317],"category_scores_gemma":[0.000529143,0.001068436,0.0002963832,0.001532478,0.0001202136,0.0003970358,0.0006867636,0.0005734796,0.0003819142],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007577667,"about_ca_system_score_gemma":0.0121386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8251541,"about_ca_topic_score_gemma":0.9990232,"domain_scores_codex":[0.9961768,0.0002078859,0.0005023536,0.001633189,0.0003028509,0.00117691],"domain_scores_gemma":[0.9956306,0.000878628,0.0008221494,0.001889549,0.0002939885,0.0004851045],"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":[0.0004363405,0.00008350461,0.0003111672,0.0009560739,0.0002375236,0.0003363519,0.000005446277,0.1852435,3.479669e-7,0.00001150544,0.8123736,0.000004589946],"study_design_scores_gemma":[0.001980382,0.0001183778,0.0004359943,0.0002528923,0.0005694857,0.000005372715,0.00003308446,0.03707975,5.045076e-7,0.000008423628,0.9583993,0.001116407],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004877476,0.00009267357,0.001669031,0.00005511346,0.001073067,0.003492119,0.993338,0.0001828026,0.00004838519],"genre_scores_gemma":[0.00003372556,0.0001292149,0.0004295824,0.00004088724,0.0004224523,0.00006096172,0.9941463,0.0002085338,0.004528324],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1738692,"threshold_uncertainty_score":0.9991766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05069176938179859,"score_gpt":0.2338195706696822,"score_spread":0.1831278012878836,"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."}}