{"id":"W3135400818","doi":"10.3390/f12030316","title":"Planning to Practice: Impacts of Large-Scale and Rapid Urban Afforestation on Greenspace Patterns in the Beijing Plain Area","year":2021,"lang":"en","type":"article","venue":"Forests","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Afforestation; Beijing; Metropolitan area; Scale (ratio); Environmental resource management; Temporal scales; Environmental science; Geography; Environmental planning; Agroforestry; Ecology; Cartography; China","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":[0.0003598344,0.00007392954,0.00009104117,0.00002647312,0.00006448316,0.00003125135,0.00008890139,0.0000333351,0.00007563794],"category_scores_gemma":[0.00005906626,0.00005002621,0.00001586975,0.00015353,0.000004788775,0.0002043225,0.0000654219,0.00006622526,0.00002153444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002787041,"about_ca_system_score_gemma":0.000005510927,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004531507,"about_ca_topic_score_gemma":0.05868433,"domain_scores_codex":[0.9992514,0.00007347222,0.0001229128,0.000163625,0.0002038472,0.0001847827],"domain_scores_gemma":[0.9995475,0.0001654826,0.00006829237,0.0001598879,0.000005956127,0.00005283987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003479928,0.0000495139,0.9873945,0.0000281912,0.000003906403,0.00004894613,0.009197483,0.002229754,0.0001373822,0.00001965836,0.0005640422,0.0002918775],"study_design_scores_gemma":[0.000280682,0.0001125197,0.9908212,0.0001593091,0.000007839265,0.00001576033,0.003396265,0.002909573,0.0004889636,0.00004820094,0.001684276,0.00007535764],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976767,0.00005152466,0.0001129382,0.001059869,0.0000438872,0.0001327412,0.00001772722,0.000006522122,0.000898127],"genre_scores_gemma":[0.9992443,0.00001248725,0.0001591751,0.0005167316,0.00002241758,0.000008438209,0.00001882644,0.000006073825,0.00001158655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05823117,"threshold_uncertainty_score":0.9584922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01140239986670886,"score_gpt":0.2647169076759256,"score_spread":0.2533145078092167,"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."}}