{"id":"W2169928132","doi":"10.1023/a:1011587222253","title":"Modeling Land-Use Change in a Decision-Support System for Coastal-Zone Management","year":2001,"lang":"en","type":"article","venue":"Environmental Modeling & Assessment","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Scale (ratio); Macro; Cellular automaton; Computer science; Environmental resource management; Land use; Land use, land-use change and forestry; Key (lock); Operations research; Geography; Environmental science; Ecology; Mathematics; Cartography; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001156835,0.0006763026,0.0007113134,0.0004576569,0.001112659,0.001730771,0.001136885,0.001691408,0.003417916],"category_scores_gemma":[0.003532112,0.0006525808,0.00062993,0.0006317318,0.000926135,0.002052349,0.0008254042,0.001052703,0.0002149101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003057539,"about_ca_system_score_gemma":0.001990916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0971876,"about_ca_topic_score_gemma":0.07767931,"domain_scores_codex":[0.9995565,0.000183221,0.00002795672,0.00008826236,0.00005766525,0.00008638559],"domain_scores_gemma":[0.9982277,0.001283697,0.0001022148,0.00005058799,0.0001683164,0.0001676416],"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":[0.0001164007,0.00009703267,0.003771336,0.00001385443,0.00002255166,0.00005863676,0.0000643164,0.9922213,0.0004743263,0.0007489456,0.0001813644,0.002229986],"study_design_scores_gemma":[0.00001213645,0.0000155107,0.0003487115,8.123531e-7,0.000007196202,0.000002903893,0.00002040582,0.9991478,0.0001369656,0.0002576908,0.00004720814,0.000002685877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690175,0.00009150887,0.02705727,0.0005644062,0.00004281411,0.00009176641,0.0003374263,0.000183541,0.002613729],"genre_scores_gemma":[0.9903412,0.00003813795,0.008252126,0.00003524212,0.00001143026,0.0000453319,0.0001248077,0.00001656074,0.001135088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0971876,"threshold_uncertainty_score":0.1932438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02952573015258362,"score_gpt":0.2657342779308034,"score_spread":0.2362085477782198,"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."}}