{"id":"W7133081884","doi":"","title":"Abscess detection on bovine livers with a commercial smart imaging system","year":2025,"lang":"en","type":"article","venue":"Charles Sturt University Research Output (CRO)","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"P&P Optica (Canada)","funders":"","keywords":"Hyperspectral imaging; Quality assurance; Quality (philosophy); Process (computing); Visual inspection; Meat packing industry; Image processing; Process control","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003131471,0.0002248803,0.0003190852,0.0008969335,0.00103038,0.0001196684,0.0006427588,0.0001281455,0.000342328],"category_scores_gemma":[0.0000762889,0.0002183256,0.0001155071,0.001677589,0.0003521166,0.0001927664,0.0003016013,0.000793435,0.00006165484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001436493,"about_ca_system_score_gemma":0.000193346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693585,"about_ca_topic_score_gemma":0.0005257795,"domain_scores_codex":[0.9979867,0.00009277122,0.0001359333,0.0005501126,0.0006273208,0.0006071698],"domain_scores_gemma":[0.9986299,0.0002722055,0.00007154312,0.0004744143,0.0003862752,0.0001656668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.03782176,0.004757367,0.5584384,0.01062408,0.008115837,0.006128185,0.01034035,0.0003786314,0.1224652,0.02206836,0.116742,0.1021199],"study_design_scores_gemma":[0.01166177,0.0008399989,0.03952747,0.002007567,0.001338856,0.00006969604,0.1332347,0.003219113,0.608665,0.00009424711,0.1972648,0.002076799],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7462652,0.0003016912,0.001217375,0.0006337633,0.00009794404,0.0002073895,0.00005878592,0.0002931134,0.2509248],"genre_scores_gemma":[0.9613529,0.00009971129,0.00003224653,0.00003971421,0.00009737165,0.000002675041,0.00001256246,0.0000170503,0.03834576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5189109,"threshold_uncertainty_score":0.8903059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02908639273599005,"score_gpt":0.2931053529464516,"score_spread":0.2640189602104615,"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."}}