{"id":"W4379375102","doi":"10.1016/j.meatsci.2023.109237","title":"Developing an alternative classification method for predicting ham composition using linear measurements from the cross-sectional ham surface","year":2023,"lang":"en","type":"article","venue":"Meat Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"Guelph Research and Development Centre, Agriculture and Agri-Food Canada; Swine Innovation Porc","keywords":"Percentile; Linear regression; Mathematics; Lean tissue; Cross-validation; Dual energy; Regression analysis; Subcutaneous fat; Statistics; Medicine; Bone mineral; Adipose tissue; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003527828,0.0001008689,0.00009535597,0.00001125981,0.001761823,0.0002731938,0.0004626905,0.00004061186,0.00001694332],"category_scores_gemma":[0.0003173102,0.00004010047,0.00004315298,0.0007463714,0.0001917997,0.0005138752,0.00008494462,0.00008397814,0.0000110436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009388327,"about_ca_system_score_gemma":0.0000427856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007869753,"about_ca_topic_score_gemma":0.0001467995,"domain_scores_codex":[0.9981832,0.0001702229,0.0002336907,0.0005293866,0.0006040746,0.0002794566],"domain_scores_gemma":[0.9990238,0.0003435581,0.0001289111,0.00007684198,0.0003626481,0.0000642329],"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":[0.00001765779,0.0000127034,0.1622782,0.000001872394,0.000003564025,8.883638e-8,0.0001723513,0.0007929228,0.8347307,0.0002578872,0.000007196556,0.001724786],"study_design_scores_gemma":[0.0000693149,0.00004185534,0.7281834,0.00001447236,0.000003974031,9.903993e-7,0.0002119914,0.1465614,0.1235339,0.001170635,0.0001076552,0.0001004523],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890783,0.00001134193,0.009191296,0.0008239863,0.0004021342,0.0002930893,0.00006427574,0.00009159247,0.00004402744],"genre_scores_gemma":[0.9812763,0.000002028995,0.01788361,0.0001605578,0.0005536316,0.000008102308,0.00008753302,0.000001082122,0.00002719641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7111969,"threshold_uncertainty_score":0.9995378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4393749052668072,"score_gpt":0.4311955306062178,"score_spread":0.008179374660589378,"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."}}