{"id":"W4409909352","doi":"10.18280/ts.420248","title":"Spatial Differentiation and Dynamic Evolution Analysis of Cropland Non-Grain Transformation in China Based on Remote Sensing Imagery","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; Transformation (genetics); Remote sensing; Geography; Environmental science; Computer science; Biology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002888593,0.0001006998,0.0001958569,0.0006068919,0.00007362768,0.00003347264,0.00003156676,0.00004759248,0.00006492461],"category_scores_gemma":[0.000008797926,0.0000834645,0.00006224939,0.000467255,0.00002866167,0.00007831387,0.000001474789,0.00007684137,9.435474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001462291,"about_ca_system_score_gemma":0.00002555361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005607658,"about_ca_topic_score_gemma":0.0115252,"domain_scores_codex":[0.9991681,0.00009386613,0.0002724729,0.000160835,0.0001729944,0.0001317057],"domain_scores_gemma":[0.9997337,0.00007081451,0.00007370688,0.00007419095,0.0000182845,0.00002927889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006161486,0.00004483839,0.1302042,0.00009936414,0.000146015,0.000006152285,0.0008198446,0.1728235,0.001904613,0.000007119915,0.0000135246,0.6933147],"study_design_scores_gemma":[0.0003665958,0.00004462689,0.490633,0.00004226256,0.0000828777,2.224073e-7,0.00002021637,0.5086446,0.00006512152,0.00005588226,0.000002854597,0.00004173025],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7671825,0.0000168168,0.2318274,0.0001296262,0.00005785761,0.0001107777,0.00002926554,0.000009459266,0.0006363158],"genre_scores_gemma":[0.9990854,0.0000102919,0.0004552861,0.00004555875,0.00001034586,2.357797e-8,0.0003801053,0.000001454512,0.00001154261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6932729,"threshold_uncertainty_score":0.8477138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003955318116972278,"score_gpt":0.1994041774660951,"score_spread":0.1954488593491228,"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."}}