{"id":"W2132562866","doi":"10.5539/jsd.v4n6p72","title":"Modelling Land Use Changes at the Peri-Urban Areas using Geographic Information Systems and Cellular Automata Model","year":2011,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Sains Malaysia","keywords":"Land use; Constraint (computer-aided design); Urban planning; Agriculture; Geography; Environmental planning; Urban area; Geographic information system; Urban expansion; Environmental resource management; Land use, land-use change and forestry; Ecology; Environmental science; Cartography","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":[0.0007191083,0.0001210973,0.0001560847,0.00009982323,0.0003634869,0.0001476691,0.0001618016,0.0000516256,0.00005145371],"category_scores_gemma":[0.00000641187,0.00007309642,0.00002615375,0.0001272196,0.00001784284,0.001209276,0.000267199,0.00008088059,0.000008652979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000252398,"about_ca_system_score_gemma":0.00004448551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007324512,"about_ca_topic_score_gemma":0.00004716425,"domain_scores_codex":[0.9989443,0.00003231949,0.0003455282,0.00008529758,0.000318364,0.0002741257],"domain_scores_gemma":[0.9993704,0.00001763536,0.0003293215,0.0001185608,0.00006610451,0.00009795817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001200358,0.00007101602,0.2891099,0.0004756712,0.0001328748,0.0001293953,0.02833427,0.6806816,0.0001336621,0.0002461032,0.0003105139,0.0002549319],"study_design_scores_gemma":[0.0004022307,0.00004691379,0.007540796,0.000140215,0.00005060024,0.0001244965,0.00807169,0.9757832,0.0005606666,0.0001448044,0.006884456,0.0002499055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961598,0.0002046668,0.003051343,0.00004181615,0.00005592515,0.0001904583,0.000001178115,0.000008896876,0.0002859414],"genre_scores_gemma":[0.9982391,0.00009866223,0.001422586,0.00004806971,0.00001729247,0.000006048984,0.000002166332,0.000007545279,0.0001585489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2951016,"threshold_uncertainty_score":0.2980786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547460687656155,"score_gpt":0.1859991903990106,"score_spread":0.1605245835224491,"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."}}