{"id":"W2465540758","doi":"10.1007/s10980-016-0400-z","title":"Multi-scale mismatches between urban sprawl and landscape fragmentation create windows of opportunity for conservation development","year":2016,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Secretaría de Estado de Investigación, Desarrollo e Innovación; Solar Energy Technologies Office; Ministerio de Educación, Cultura y Deporte","keywords":"Urban sprawl; Landscape ecology; Fragmentation (computing); Nature Conservation; Sustainable development; Scale (ratio); Environmental planning; Geography; Environmental resource management; Urban planning; Environmental science; Ecology; Biology; Cartography; Habitat","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":[],"consensus_categories":[],"category_scores_codex":[0.0003158717,0.0001155186,0.0002372777,0.00003587315,0.000106055,0.000009832623,0.0001046557,0.0001103727,0.0007981836],"category_scores_gemma":[0.00002272776,0.00007583841,0.00002817829,0.0000559036,0.000025659,0.0001610807,0.00007423665,0.00002720663,0.00005052092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002757249,"about_ca_system_score_gemma":0.00002304441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007319679,"about_ca_topic_score_gemma":0.003339833,"domain_scores_codex":[0.9991094,0.00005047361,0.0003042508,0.0002365085,0.00008765743,0.0002117032],"domain_scores_gemma":[0.9993597,0.0002238845,0.0001783679,0.0001185638,0.00001594626,0.0001035954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003588005,0.00004270483,0.9939203,0.00004517876,0.00002762888,5.962492e-7,0.0005417003,0.000006184787,0.002411983,0.000002301759,0.001036872,0.001928723],"study_design_scores_gemma":[0.001631357,0.000112099,0.9863704,0.00002181355,0.00002859279,0.000002186069,0.0001843808,0.0005786861,0.005305687,0.00006713525,0.005564765,0.0001329096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979276,0.00002284058,0.0006323426,0.0005524325,0.00008207613,0.0003316508,0.0000379367,0.00002348529,0.0003896558],"genre_scores_gemma":[0.9965842,0.00002449384,0.002851071,0.0001447032,0.00004461422,0.00006769049,0.00006314979,0.00001006127,0.0002100272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007549858,"threshold_uncertainty_score":0.873955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0236610272920627,"score_gpt":0.237375508409804,"score_spread":0.2137144811177412,"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."}}