{"id":"W2342265936","doi":"10.2166/wqrj.2010.002","title":"Evaluation of Risk Assessment Tools to Predict Canadian Waterborne Disease Outbreaks","year":2010,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canadian Water Network","keywords":"Risk assessment; Waterborne diseases; Outbreak; Environmental health; Risk analysis (engineering); Water quality; Environmental science; Environmental planning; Water contamination; Contamination; Business; Computer science; Medicine; Computer security; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.05754601,0.0001388236,0.0001943643,0.0002267261,0.0005429289,0.0003049354,0.0005683925,0.00008729679,0.009651275],"category_scores_gemma":[0.002461593,0.00009260669,0.0001235003,0.0002248589,0.0002732166,0.0005427294,0.0002651369,0.001132994,0.0006080751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008492413,"about_ca_system_score_gemma":0.0003592327,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06613868,"about_ca_topic_score_gemma":0.09750695,"domain_scores_codex":[0.9899526,0.004246328,0.0006288248,0.0003414848,0.004056024,0.0007747055],"domain_scores_gemma":[0.9969579,0.0001647732,0.00009042646,0.0004994052,0.0006154439,0.001672039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002087389,0.0005126112,0.7030802,0.00003450157,0.00009965034,0.00003421375,0.007274856,0.00100978,0.0738584,0.0006437933,0.005971924,0.2072713],"study_design_scores_gemma":[0.000632777,0.00008609635,0.9718,0.00001419139,0.00003707246,0.000004853009,0.0002077637,0.001102602,0.009474646,0.008570991,0.007909052,0.0001599663],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877402,0.000003453865,0.0002574635,0.005112271,0.000285422,0.0005118842,0.0001287326,0.0000114475,0.005949182],"genre_scores_gemma":[0.9988039,0.000004868441,0.000467568,0.0001462217,0.0001416367,0.00003736311,0.00003322007,0.00001306588,0.0003521203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2687197,"threshold_uncertainty_score":0.991254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.149561767137694,"score_gpt":0.4390851093855012,"score_spread":0.2895233422478072,"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."}}