{"id":"W2790566020","doi":"","title":"Green infrastructure, climate change and spatial planning:","year":2017,"lang":"en","type":"article","venue":"Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)","topic":"Water Governance and Infrastructure","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Universidade de Lisboa; Centro de Investigação em Ciências Sociais; Fundação para a Ciência e a Tecnologia; Faculty of Arts, Ryerson University","keywords":"Climate change; Green infrastructure; Environmental planning; Environmental resource management; Business; Geography; Environmental science; Geology","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.004317306,0.0001794048,0.0002147379,0.001107646,0.006697793,0.000517887,0.001205712,0.0002955631,0.00002135674],"category_scores_gemma":[0.002919179,0.0001567555,0.00003215326,0.0009172911,0.005741837,0.001438145,0.0006395103,0.0004696645,0.000003614241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000196929,"about_ca_system_score_gemma":0.0008080025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002742269,"about_ca_topic_score_gemma":0.0003831916,"domain_scores_codex":[0.9962867,0.00004548489,0.0002658349,0.0007138398,0.001488781,0.001199365],"domain_scores_gemma":[0.9982291,0.0001278318,0.0002464975,0.0002994663,0.0008935821,0.0002035291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001100616,0.00007529775,0.2947221,0.000108783,0.00003925428,0.0000253096,0.005031534,2.472111e-7,0.004032589,0.3175364,0.01074807,0.3675703],"study_design_scores_gemma":[0.001577444,0.001076446,0.3279204,0.0002289576,0.00001872962,0.00004718455,0.002775372,0.00100181,0.003029058,0.4833957,0.178091,0.0008378812],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9185194,0.002546278,0.000166476,0.0113193,0.0008319761,0.002711151,0.0005666607,0.0002844694,0.06305431],"genre_scores_gemma":[0.9958762,0.001566699,0.0005584678,0.0000553028,0.0004274,0.0002357719,0.00001993907,0.00001463671,0.001245582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3667324,"threshold_uncertainty_score":0.996964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09423257406211322,"score_gpt":0.4033110366761868,"score_spread":0.3090784626140736,"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."}}