{"id":"W4404879202","doi":"10.1016/j.atech.2024.100683","title":"Predicting main behaviors of beef bulls from accelerometer data: A machine learning framework","year":2024,"lang":"en","type":"article","venue":"Smart Agricultural Technology","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Accelerometer; Computer science; Artificial intelligence; Machine learning; Operating system","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":[0.0008874595,0.0007599787,0.0005440634,0.0009706343,0.0002786017,0.0006116926,0.0008864161,0.0007814581,0.0006130943],"category_scores_gemma":[0.001308271,0.0002451941,0.000648981,0.0005696274,0.0002792413,0.0004539493,0.0004278626,0.000766666,0.0002554671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006149019,"about_ca_system_score_gemma":0.0006457283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01952477,"about_ca_topic_score_gemma":0.01557652,"domain_scores_codex":[0.9996411,0.00007236331,0.00002532415,0.0001418372,0.00006340871,0.00005593868],"domain_scores_gemma":[0.9994673,0.0002412809,0.00007712978,0.00002864576,0.0001506417,0.00003509363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003804739,0.0008603431,0.05897553,0.0001975302,0.0002490891,0.0002783654,0.0001842223,0.5856175,0.01114404,0.001681154,0.002245485,0.3381861],"study_design_scores_gemma":[0.000004876488,0.0000734862,0.006823802,0.000008214259,0.00001426456,0.00001800113,0.00002042902,0.9919527,0.0004421518,0.0004359487,0.0001982762,0.000007865725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3825375,0.001204501,0.6114677,0.0005907725,0.00007992217,0.0002080782,0.001560537,0.001110408,0.001240491],"genre_scores_gemma":[0.8656394,0.0004170714,0.1301215,0.00008619233,0.00008717981,0.0002166013,0.001885021,0.00001929477,0.001527607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01952477,"threshold_uncertainty_score":0.03882223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319312418759205,"score_gpt":0.2466370870267258,"score_spread":0.2234439628391338,"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."}}