{"id":"W4300082173","doi":"10.3389/fvets.2022.962989","title":"Comparing behavioral risk assessment strategies for quantifying biosecurity compliance to mitigate animal disease spread","year":2022,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Institute of Food and Agriculture; U.S. Department of Agriculture","keywords":"Biosecurity; Context (archaeology); Risk assessment; Disease; Protocol (science); Outbreak; Environmental health; Medicine; Psychology; Business; Actuarial science; Computer science; Biology; Computer security; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.001036161,0.0001600164,0.0002456845,0.00008414525,0.001134449,0.0001457588,0.0008287106,0.00001760906,0.0000516666],"category_scores_gemma":[0.00004243791,0.00009323013,0.00008782253,0.0008626687,0.00028758,0.0004624573,0.0006997038,0.0001611312,0.000002996627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001635195,"about_ca_system_score_gemma":0.00005502254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002458477,"about_ca_topic_score_gemma":0.00005387732,"domain_scores_codex":[0.9980332,0.0001736921,0.0002579053,0.0006489812,0.0002974501,0.0005887256],"domain_scores_gemma":[0.9994525,0.00005920522,0.0001111128,0.00009938782,0.00003637746,0.0002413629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008408587,0.0003491896,0.9450225,0.00003384197,0.000006907775,0.00005580868,0.000185197,0.001443614,0.03851686,0.003046699,0.002621623,0.00787689],"study_design_scores_gemma":[0.0001419422,0.001735767,0.9487658,0.00001730864,0.0000119489,0.000001501215,0.002745556,0.03876014,0.000004710744,0.001508763,0.006067765,0.0002387723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967123,0.0001293696,0.0009059692,0.0006158912,0.0005747331,0.0005735312,0.0002254162,0.00005770907,0.0002051047],"genre_scores_gemma":[0.9947475,0.000009944553,0.004721643,0.0002174206,0.00004772086,0.0001841619,0.00004761413,0.000001410374,0.00002262765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03851215,"threshold_uncertainty_score":0.8725383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1964069569937113,"score_gpt":0.3750921095782166,"score_spread":0.1786851525845053,"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."}}