{"id":"W4316664152","doi":"10.3390/land12010262","title":"Swelling Cities? Detecting China’s Urban Land Transition Based on Time Series Data","year":2023,"lang":"en","type":"article","venue":"Land","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"China; Land use; Urban planning; Geography; Transition (genetics); Land use, land-use change and forestry; Stage (stratigraphy); Economic geography; Land development; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002340019,0.0000826477,0.0000922943,0.00002422847,0.0001636817,0.00005226171,0.0001834242,0.0000386409,0.0007231397],"category_scores_gemma":[0.000005663204,0.00006257731,0.00001715219,0.0001496325,0.000007022937,0.0002532289,0.00005657284,0.00005854396,0.001322408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001592281,"about_ca_system_score_gemma":0.000003003325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001117392,"about_ca_topic_score_gemma":0.002373744,"domain_scores_codex":[0.9993171,0.00002873565,0.00009618529,0.0002238755,0.0001520298,0.0001820445],"domain_scores_gemma":[0.9996102,0.00003289,0.00002971473,0.0002837142,0.000001283767,0.0000422023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001706473,0.00005003759,0.9016858,0.0001864846,0.00002622315,0.00007921292,0.002101271,0.08817063,0.001538741,0.000001819577,0.003545858,0.002443267],"study_design_scores_gemma":[0.0006608833,0.0001319912,0.1783333,0.0001330811,0.00002728296,0.000007180975,0.00008597654,0.8117978,0.0009532173,0.0001408736,0.007419324,0.000309107],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957194,0.000008385869,0.00007339329,0.0003525995,0.00008273954,0.00007872201,0.00006943734,0.0001248264,0.003490446],"genre_scores_gemma":[0.9992034,0.000009291025,0.00005641465,0.0001212061,0.0001138425,0.000003930968,0.0002414234,0.00001130451,0.0002391627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7236272,"threshold_uncertainty_score":0.9994552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434319824369787,"score_gpt":0.2060844895606487,"score_spread":0.1917412913169508,"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."}}