{"id":"W2264477083","doi":"","title":"India’ Exports of Live Stock and Allied Products","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Agricultural Economics and Practices","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Geography; Agriculture; Agricultural economics; Business; Livestock; Stock (firearms); Sri lanka; Socioeconomics; Economics; Tanzania","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":[0.0001242254,0.0002660917,0.0001248668,0.002500157,0.0003653331,0.001375233,0.0002279937,0.0001667679,0.004825898],"category_scores_gemma":[0.0004519558,0.0001283558,0.0004396361,0.005455191,0.0001858995,0.0006400055,0.0005042377,0.0003337035,0.0008226865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007261657,"about_ca_system_score_gemma":0.0006791095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0137582,"about_ca_topic_score_gemma":0.01425578,"domain_scores_codex":[0.9998091,0.00001405505,0.0000160152,0.00003194734,0.00006924893,0.00005973418],"domain_scores_gemma":[0.9994619,0.00008407471,0.0001982563,0.00005483372,0.0001641755,0.00003671901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005864663,0.0001832305,0.7656493,0.001145656,0.0002557285,0.00516356,0.008638961,0.003657495,0.0103198,0.01073018,0.01577739,0.1778923],"study_design_scores_gemma":[0.000005226885,0.00008891863,0.9408597,0.00008206338,0.00006406902,0.001789019,0.003071509,0.0005156558,0.002030661,0.0004394803,0.05103772,0.00001606131],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9431736,0.001225162,0.0003217774,0.0002578502,0.00002352222,0.00001897428,0.007614008,0.00006541563,0.0472996],"genre_scores_gemma":[0.967342,0.002598208,0.0005596698,0.0001113549,0.00002637183,0.00001597019,0.009427803,0.00002730866,0.01989132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0137582,"threshold_uncertainty_score":0.02735621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001829105863067,"score_gpt":0.1990671189780044,"score_spread":0.1890488279193737,"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."}}