{"id":"W4295813842","doi":"10.3390/ani12182386","title":"Applying Machine Learning Algorithms for the Classification of Mink Infected with Aleutian Disease Using Different Data Sources","year":2022,"lang":"en","type":"article","venue":"Animals","topic":"Animal Virus Infections Studies","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Nova Scotia Mink Breeders Association; Mitacs; Canada Mink Breeders Association","keywords":"Mink; Machine learning; Artificial intelligence; Boosting (machine learning); Naive Bayes classifier; Random forest; Statistical classification; Support vector machine; American mink; Decision tree; Algorithm; Computer science; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002106688,0.00009724092,0.0001243266,0.00001109773,0.00124909,0.00002903744,0.000281545,0.00001324317,0.0001032936],"category_scores_gemma":[0.00007638003,0.00003220208,0.000041716,0.0002293771,0.00007684289,0.00005804729,0.0003417997,0.0001060758,6.925563e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002317248,"about_ca_system_score_gemma":0.000006975307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003848208,"about_ca_topic_score_gemma":0.0003978209,"domain_scores_codex":[0.999213,0.00008605251,0.0001462661,0.0002381054,0.000168403,0.000148167],"domain_scores_gemma":[0.9992958,0.000380875,0.0001554023,0.00009045583,0.00004555216,0.00003186963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003321382,0.0002207537,0.5975828,0.00002740107,0.000161303,0.000001238295,0.0002033013,0.0006124836,0.343554,0.0005123331,0.00008428728,0.05670801],"study_design_scores_gemma":[0.0001343211,0.0004540468,0.9261764,0.00001078792,0.0001242186,0.000003029338,0.001359049,0.04408568,0.0003123988,0.00004830804,0.02715525,0.0001364982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975414,0.0008443126,0.0003700736,0.0002914214,0.00002696846,0.0005460617,0.0003092432,0.00004258327,0.00002798243],"genre_scores_gemma":[0.9993346,0.00003649626,0.0001084056,0.0000349994,0.00008123182,0.0002210403,0.0001439072,0.000001678454,0.00003764303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3432416,"threshold_uncertainty_score":0.9607119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1537652027501421,"score_gpt":0.2989201347447649,"score_spread":0.1451549319946227,"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."}}