{"id":"W4413194581","doi":"10.15832/ankutbd.1472606","title":"The Impacts of Agricultural Energy Use and Cultivable Area on the Cropland Footprint in Light of the EKC Model: Evidence from the Top Ten Most Successful Countries in Agriculture","year":2025,"lang":"en","type":"article","venue":"Tarım Bilimleri Dergisi","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Footprint; Agricultural economics; Environmental science; Ecological footprint; Natural resource economics; Geography; Agricultural engineering; Agroforestry; Environmental protection; Economics; Ecology; Sustainability; Engineering; Biology; 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":[0.001851192,0.0004335342,0.0003762553,0.0008894094,0.0005027226,0.001533293,0.0004674121,0.0003393217,0.00277195],"category_scores_gemma":[0.004627201,0.000148195,0.000756297,0.002099023,0.001354082,0.001115449,0.001185006,0.0006115658,0.0003384298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009711818,"about_ca_system_score_gemma":0.001196556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04593171,"about_ca_topic_score_gemma":0.04315596,"domain_scores_codex":[0.9992982,0.0002735003,0.00003605506,0.0001257494,0.00008426794,0.0001822281],"domain_scores_gemma":[0.9956405,0.002336885,0.0009496259,0.0003293951,0.0005555148,0.0001880974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000237056,0.00008902325,0.9655518,0.00008369016,0.0003180924,0.000601472,0.0006319097,0.01445209,0.0002782246,0.00551635,0.0006923412,0.01154798],"study_design_scores_gemma":[0.00003564304,0.0002982929,0.9484999,0.0001063392,0.000382743,0.0002930168,0.01222482,0.02859778,0.0008557952,0.004092895,0.004572926,0.00003992295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944862,0.0003570798,0.0005520979,0.0001815227,0.000006439707,0.000007340152,0.0002180642,0.000007377445,0.004183996],"genre_scores_gemma":[0.9992633,0.0001738269,0.0001373642,0.00001725187,0.000003267374,0.000003253755,0.000233249,0.000002997093,0.0001655031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04593171,"threshold_uncertainty_score":0.09132868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007591224310865024,"score_gpt":0.2102336412005192,"score_spread":0.2026424168896542,"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."}}