{"id":"W4406261983","doi":"10.1109/bibm62325.2024.10822176","title":"Ensemble learning for heterogeneous biomarker discovery in precision dairy farming","year":2024,"lang":"en","type":"article","venue":"","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Ensemble learning; Precision agriculture; Biomarker; Biomarker discovery; Machine learning; Agriculture; Artificial intelligence; Chemistry; Biology; Ecology; Proteomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004076984,0.001172162,0.00162817,0.001917954,0.0004817468,0.001141279,0.001180036,0.0009074321,0.001064423],"category_scores_gemma":[0.006998839,0.0004630626,0.001164311,0.00187522,0.000293905,0.001076411,0.00133183,0.001150661,0.000463891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006048249,"about_ca_system_score_gemma":0.0008336366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005773917,"about_ca_topic_score_gemma":0.006196465,"domain_scores_codex":[0.998773,0.0004669261,0.00007844558,0.0004010896,0.00018842,0.00009203478],"domain_scores_gemma":[0.9968718,0.001816267,0.0002781169,0.0005262318,0.0004238286,0.0000839623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003699345,0.000222084,0.02391011,0.0002059221,0.0007615466,0.0002031254,0.0001066554,0.6240914,0.005163478,0.003208142,0.005032934,0.3367246],"study_design_scores_gemma":[0.00001315214,0.00006134334,0.002431205,0.00002039174,0.00006070254,0.00002856201,0.00001694105,0.9870858,0.001239804,0.007732045,0.001293734,0.00001629829],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08975051,0.003370177,0.8982193,0.0006969145,0.0001724749,0.000114471,0.003126822,0.002850542,0.001698859],"genre_scores_gemma":[0.7688251,0.001350084,0.2201538,0.0003350534,0.0002232281,0.0002747911,0.006681585,0.0001430361,0.002013221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005773917,"threshold_uncertainty_score":0.02156144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02995329926872489,"score_gpt":0.2637424891968401,"score_spread":0.2337891899281152,"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."}}