{"id":"W4393352732","doi":"10.56825/bufbu.2024.4314847","title":"Scoping study of research trends on Nili Ravi buffalo applying scientometric analysis and network visualization","year":2024,"lang":"en","type":"article","venue":"Buffalo Bulletin","topic":"Agricultural Economics and Practices","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visualization; Social network analysis; Regional science; Data science; Geography; Computer science; Data mining; World Wide Web","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02453708,0.0005444732,0.001722562,0.09408464,0.002430766,0.006164924,0.001135242,0.0009085741,0.002909543],"category_scores_gemma":[0.07234932,0.0004545399,0.001703679,0.1093839,0.001179041,0.00382981,0.002530056,0.0004998122,0.0005114331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003395501,"about_ca_system_score_gemma":0.01423531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007726397,"about_ca_topic_score_gemma":0.01012051,"domain_scores_codex":[0.9855897,0.00330241,0.00465657,0.00109077,0.004743882,0.0006168159],"domain_scores_gemma":[0.8873167,0.07399298,0.01543746,0.002758865,0.01941542,0.001078495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006923989,0.0002065063,0.2511112,0.1262335,0.002529909,0.003959721,0.03589789,0.002224346,0.005446463,0.01301689,0.01474036,0.5439407],"study_design_scores_gemma":[0.00007994461,0.0009163793,0.536044,0.1241332,0.009343504,0.004707066,0.1024865,0.006056468,0.009263152,0.010743,0.195891,0.0003356738],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.659435,0.2340478,0.01313999,0.005908718,0.0004747388,0.007923277,0.03032063,0.0003638467,0.04838601],"genre_scores_gemma":[0.8699682,0.09411556,0.01431443,0.0004836805,0.0002362039,0.004616324,0.01248194,0.0000863216,0.003697348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9059154,"threshold_uncertainty_score":0.129766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0785497497776097,"score_gpt":0.3675653181611184,"score_spread":0.2890155683835087,"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."}}