{"id":"W4406563995","doi":"10.1016/j.atech.2025.100786","title":"Smart glasses in the chicken barn: Enhancing animal welfare through mixed reality","year":2025,"lang":"en","type":"article","venue":"Smart Agricultural Technology","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Ernährung und Landwirtschaft; Bundesanstalt für Landwirtschaft und Ernährung; University of Saskatchewan","keywords":"Barn; Animal welfare; Welfare; Business; Economics; Biology; Engineering; Market economy; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000446212,0.0007168801,0.0003248648,0.0003768399,0.0001844691,0.0008598533,0.0009304082,0.0007696952,0.003914296],"category_scores_gemma":[0.0007938385,0.0003128859,0.0006276742,0.0001204994,0.0003388769,0.0007508504,0.001265401,0.0003669457,0.0007051327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002149847,"about_ca_system_score_gemma":0.0002573612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001323953,"about_ca_topic_score_gemma":0.002828187,"domain_scores_codex":[0.9995994,0.0001144107,0.00001481849,0.00009123232,0.0001293544,0.00005074358],"domain_scores_gemma":[0.999746,0.0001035326,0.00002736893,0.00002777584,0.00004625359,0.00004900832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001073316,0.0008507087,0.0112129,0.001283193,0.0001621644,0.001107253,0.002614105,0.005465178,0.6700085,0.002175755,0.00506048,0.2989865],"study_design_scores_gemma":[0.0004952101,0.0136223,0.1603926,0.001334198,0.001424178,0.007392969,0.004157474,0.2843043,0.4091103,0.005191924,0.1115923,0.0009823703],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4947505,0.001492814,0.4846679,0.0008710206,0.0003252971,0.0009171971,0.0007363015,0.003368018,0.01287103],"genre_scores_gemma":[0.6902245,0.0008278883,0.2986746,0.000607724,0.00006642306,0.0006043126,0.0003532629,0.0001903883,0.008450893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003914296,"threshold_uncertainty_score":0.0130946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01333525086759958,"score_gpt":0.3139662992983707,"score_spread":0.3006310484307711,"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."}}