{"id":"W4236185271","doi":"10.1142/s021903030200071x","title":"General Information & Statistics","year":2002,"lang":"en","type":"article","venue":"Asia-Pacific Biotech News","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Summit; Beijing; Agriculture; Mainland China; Biotechnology; Political science; Economic growth; Geography; Business; Agricultural economics; Economics; Biology; Cartography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001817303,0.0009350462,0.001493813,0.008733025,0.0007389914,0.00181626,0.001749644,0.001183842,0.3584783],"category_scores_gemma":[0.01452958,0.0006238632,0.0007172758,0.01447145,0.0004447641,0.001673231,0.0008853585,0.001565809,0.3096572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002018378,"about_ca_system_score_gemma":0.004137014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03091807,"about_ca_topic_score_gemma":0.0221159,"domain_scores_codex":[0.9980454,0.0002317084,0.0003774311,0.0003431172,0.0007550244,0.0002473238],"domain_scores_gemma":[0.9899462,0.002243856,0.001048394,0.0006280797,0.005218692,0.0009148465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003156183,0.00001479896,0.0004957301,0.0003107831,0.00000352803,0.00001659143,0.000006986493,0.00006236181,0.00002786728,0.0002084236,0.9903978,0.008423603],"study_design_scores_gemma":[0.00006553431,0.00006108241,0.0158614,0.0005989527,0.00001166025,0.00009512153,0.00005443965,0.0001747743,0.000110958,0.0008750187,0.9820685,0.00002264812],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0007304463,0.002169097,0.0005741935,0.003399244,0.001949845,0.0007327229,0.9110927,0.0009064705,0.07844533],"genre_scores_gemma":[0.005574763,0.00608236,0.0009977504,0.006488487,0.001657323,0.002224619,0.7615396,0.00063193,0.2148031],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3584783,"threshold_uncertainty_score":0.9150529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694662462992024,"score_gpt":0.2391943570156288,"score_spread":0.2222477323857086,"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."}}