{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001711779,0.0002399108,0.0002606254,0.00008234002,0.000283764,0.00003849303,0.0004560795,0.0003345305,0.00002053615],"category_scores_gemma":[0.0002425416,0.0001444925,0.0001093377,0.0005608381,0.0001984194,0.00001324534,0.0003544328,0.0003660955,0.00002366788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005202717,"about_ca_system_score_gemma":0.00002484989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001959565,"about_ca_topic_score_gemma":0.006222735,"domain_scores_codex":[0.9986167,0.0001108446,0.0003147953,0.0004783395,0.0001152354,0.0003640823],"domain_scores_gemma":[0.9993403,0.0000296183,0.00009664905,0.0003743942,0.0001426022,0.00001645729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001160687,0.0001437308,0.01380629,0.00003933712,0.0001746273,0.00001340024,0.0002466871,0.000002527922,0.9401727,0.01463919,0.02981247,0.0008329491],"study_design_scores_gemma":[0.0004007528,0.0003127826,0.3751198,0.00003827602,0.00003407042,0.00005631845,0.00614321,0.000001792255,0.3174452,0.0003902588,0.2997848,0.0002727133],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9595708,0.0006985673,0.00004118602,0.0285191,0.0003214653,0.0002896063,0.00001004642,0.00009003579,0.01045923],"genre_scores_gemma":[0.9982145,0.0001270676,0.0001667373,0.0003868105,0.0001076773,0.0001312317,0.00005132141,0.000007607223,0.0008070239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6227275,"threshold_uncertainty_score":0.5892233,"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."}}