{"id":"W2283229213","doi":"","title":"World production of pig meat and its tendencies","year":2004,"lang":"en","type":"article","venue":"Tehnologija mesa","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pig iron; China; Geography; Agricultural economics; Environmental protection; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003900822,0.000191107,0.00009213471,0.003255449,0.0001942567,0.000926158,0.0001450183,0.0001555447,0.00184935],"category_scores_gemma":[0.0008321243,0.0001233722,0.0003111953,0.004061636,0.0003276918,0.0007436444,0.0003816947,0.0002178547,0.000380744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003489321,"about_ca_system_score_gemma":0.0001485151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001843781,"about_ca_topic_score_gemma":0.002392618,"domain_scores_codex":[0.9998,0.0000274246,0.00002542687,0.00006778863,0.00004985276,0.00002954952],"domain_scores_gemma":[0.9993186,0.0001160834,0.0003338207,0.00003591516,0.0001390035,0.00005655785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001633552,0.00002847399,0.9362673,0.0002485873,0.0001651812,0.0004065547,0.001218115,0.001067373,0.002240114,0.002612647,0.001455012,0.05412735],"study_design_scores_gemma":[0.000002642259,0.00008635017,0.9815994,0.00004982588,0.00004453234,0.0006420345,0.0008177903,0.0004173792,0.0006078591,0.0005027412,0.01521771,0.00001169649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9584445,0.007762763,0.0009850665,0.0004609136,0.00005213377,0.00001409976,0.003048029,0.00007638673,0.02915619],"genre_scores_gemma":[0.9908769,0.003567081,0.0008587218,0.00005380792,0.00004633634,0.00001334293,0.001905395,0.00001079384,0.002667631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003255449,"threshold_uncertainty_score":0.006186724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02758210924785399,"score_gpt":0.2158280801873498,"score_spread":0.1882459709394958,"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."}}