{"id":"W4415680841","doi":"10.1016/j.measurement.2025.119502","title":"Robust detection of dead broilers in caged environments using infrared–visible image fusion and computer vision","year":2025,"lang":"en","type":"article","venue":"Measurement","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of British Columbia; National Natural Science Foundation of China","keywords":"Robustness (evolution); Fusion; Image fusion; Broiler; Image sensor; Image processing; Machine vision","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":[0.0002010021,0.00006447568,0.0001025955,0.00002116892,0.00007222366,0.00001002616,0.00004515612,0.00004008569,0.00003491393],"category_scores_gemma":[0.000007378907,0.00003061087,0.00002242946,0.0001264705,0.00003544569,0.0000524611,0.00004689939,0.00005391989,0.000001702573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005405097,"about_ca_system_score_gemma":0.000002849724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002475397,"about_ca_topic_score_gemma":0.0002940454,"domain_scores_codex":[0.9993937,0.0000814156,0.0001460876,0.0001507575,0.0001314513,0.00009656086],"domain_scores_gemma":[0.9998712,0.00001734042,0.00004259033,0.00002510194,0.00002106604,0.00002272005],"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":[0.00007282065,0.00009568503,0.002405456,0.00001104634,0.000003224188,4.497096e-7,0.00001175749,0.00006310176,0.9858944,0.000005212558,0.00003969185,0.0113972],"study_design_scores_gemma":[0.0004599004,0.0005370724,0.9242287,0.0001201057,0.000007435121,8.291822e-7,0.00006727842,0.00303442,0.07000836,0.0002003657,0.001244379,0.00009114952],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985695,0.0001317311,0.0008921414,0.00007147996,0.00005434867,0.0001325643,0.000002446772,0.000005848942,0.0001398942],"genre_scores_gemma":[0.9996043,0.00004360142,0.0002196141,0.00008974798,0.00002085381,0.000002843577,0.00000410572,3.52199e-7,0.00001455214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9218233,"threshold_uncertainty_score":0.1248275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04481635360496436,"score_gpt":0.2255864681865571,"score_spread":0.1807701145815927,"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."}}