{"id":"W1971522472","doi":"10.1038/srep00527","title":"Fractal cartography of urban areas","year":2012,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; Federation for the Humanities and Social Sciences","keywords":"Pace; Metropolitan area; Process (computing); Computer science; Cartography; Geography; Representation (politics); Data science; Urban planning; Political science; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007854219,0.00007655936,0.0001127293,0.00004632227,0.0001331236,0.00003981991,0.0001055275,0.00003687791,0.002159128],"category_scores_gemma":[0.00001163945,0.00005670479,0.00008006176,0.0003706354,0.00006434767,0.0004117567,0.0000956701,0.00003627877,0.0002460311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001731018,"about_ca_system_score_gemma":0.000006433867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002499945,"about_ca_topic_score_gemma":0.0001102452,"domain_scores_codex":[0.9987752,0.00001860759,0.0002693503,0.0002579784,0.0003963938,0.0002824297],"domain_scores_gemma":[0.9991607,0.000009827592,0.000189461,0.0004850302,0.000009811193,0.0001451653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001248157,0.00006294827,0.9827366,0.0000101436,0.000005214692,0.00001036949,0.0005031344,0.00001849666,0.004730397,0.000006986984,0.0116262,0.0002882292],"study_design_scores_gemma":[0.000104189,0.00002782768,0.6007008,0.00003492437,0.00003742386,0.0001808747,0.0002222921,0.000115862,0.04585084,0.0012325,0.3511921,0.000300417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745444,0.0001468459,0.000008858936,0.00001452987,0.003313671,0.00009106231,0.000001316235,0.00002392129,0.02185537],"genre_scores_gemma":[0.9994848,0.000001037016,0.0000944675,0.00001397029,0.00006303419,0.000005230447,0.00001133314,0.000005627257,0.0003205426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3820359,"threshold_uncertainty_score":0.998753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007710549407082543,"score_gpt":0.2041318487600361,"score_spread":0.1964212993529535,"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."}}