{"id":"W2130569257","doi":"10.1017/s0043933910000498","title":"Past and future of poultry meat harvesting technologies","year":2010,"lang":"en","type":"article","venue":"World s Poultry Science Journal","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Meat packing industry; Poultry farming; Stunning; Process (computing); Poultry meat; Scalding; Agricultural engineering; Computer science; Business; Biotechnology; Environmental science; Engineering; Food science; Biology; Veterinary medicine; Medicine","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":[0.0004362774,0.0001031116,0.0001499708,0.00006439513,0.0005861288,0.0001139067,0.0004631599,0.00007611911,0.0001917696],"category_scores_gemma":[0.00008423907,0.00003823198,0.00005094335,0.000869608,0.0008034953,0.0003686357,0.0001000884,0.0005520691,0.000005684118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006462971,"about_ca_system_score_gemma":0.00002078152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001406088,"about_ca_topic_score_gemma":0.00008256613,"domain_scores_codex":[0.9990109,0.00002114976,0.0002161052,0.0002098675,0.0002485021,0.0002935301],"domain_scores_gemma":[0.9994082,0.000086186,0.0001672343,0.00005049704,0.0001639981,0.0001239074],"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":[0.00001019786,0.00002462525,0.1377904,0.000001997312,0.000001396489,0.000002147925,0.00002323844,1.404092e-7,0.7711257,0.002418187,0.0003663051,0.08823567],"study_design_scores_gemma":[0.0001468859,0.0001753587,0.9035081,0.00002652633,0.00000550691,0.0003427515,0.005869967,0.00001036716,0.005510417,0.003661079,0.08056989,0.0001731487],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884055,0.0001660501,9.428343e-7,0.008104281,0.0003913659,0.00004610046,0.000005514237,0.00005010532,0.002830124],"genre_scores_gemma":[0.997438,0.00009470978,0.001270687,0.0001792799,0.0007511855,8.778267e-7,0.000001167803,5.309341e-7,0.0002635915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7657177,"threshold_uncertainty_score":0.4508088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129698304372928,"score_gpt":0.2270912967105543,"score_spread":0.215794313666825,"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."}}