{"id":"W4212894930","doi":"10.33423/jabe.v23i4.4480","title":"In Pursuit of the World’s Best Steak – Advanced Robotics and X-ray Technology to Transform an Industry","year":2021,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Pittsburgh; Johns Hopkins University","keywords":"Automation; Robotics; Traceability; Productivity; Investment (military); Artificial intelligence; Meat packing industry; Engineering; Manufacturing engineering; Robot; Business; Computer science; Mechanical engineering; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004242802,0.0006082933,0.0004210498,0.0009487018,0.002258311,0.006253082,0.0007583852,0.003053574,0.0135275],"category_scores_gemma":[0.002425984,0.0005110379,0.0006677572,0.000691885,0.003781385,0.004895409,0.002978445,0.0031784,0.006514295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00266583,"about_ca_system_score_gemma":0.004812744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006779389,"about_ca_topic_score_gemma":0.01089522,"domain_scores_codex":[0.9980472,0.00031148,0.00006103424,0.0002689649,0.00108732,0.0002239111],"domain_scores_gemma":[0.9974411,0.0003789051,0.0002315711,0.0003177676,0.001009916,0.00062068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002941679,0.0003763025,0.008884353,0.001137316,0.0001056705,0.0007232717,0.003636768,0.00127297,0.08501621,0.2348002,0.1474538,0.5162988],"study_design_scores_gemma":[0.0000177071,0.0005577044,0.01022389,0.0005471965,0.00003312014,0.00104699,0.002017659,0.002163971,0.02085485,0.02597404,0.936477,0.00008594373],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1184302,0.05864789,0.1889322,0.2638583,0.007079117,0.0004299569,0.0003777456,0.00270361,0.3595409],"genre_scores_gemma":[0.3866771,0.03084812,0.1852366,0.03056279,0.0009727204,0.00009005398,0.0003350337,0.0007054707,0.3645722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0135275,"threshold_uncertainty_score":0.04525393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01134005318747109,"score_gpt":0.2521151106783764,"score_spread":0.2407750574909054,"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."}}