{"id":"W6908833842","doi":"10.3389/fenvs.2019.00093.s001","title":"Data_Sheet_1_How Land Cover Spatial Resolution Affects Mapping of Urban Ecosystem Service Flows.PDF","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Land cover; Ecosystem services; Land use; Image resolution; Spatial ecology; Geographic information system; Spatial analysis; Spatial variability; Urban area","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003780113,0.0008378021,0.0007215814,0.002819021,0.0006403966,0.001624026,0.001614367,0.000620096,0.1657023],"category_scores_gemma":[0.01137392,0.0007189339,0.0008795559,0.006866106,0.0002594648,0.001398769,0.0008932741,0.0006163835,0.05360354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001015618,"about_ca_system_score_gemma":0.001468318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04122761,"about_ca_topic_score_gemma":0.05152282,"domain_scores_codex":[0.9985552,0.0002721752,0.0001517073,0.000171944,0.0007209862,0.0001279507],"domain_scores_gemma":[0.9924838,0.003203173,0.0004182806,0.0007270634,0.003036893,0.0001309047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001363792,0.00009830504,0.01042785,0.0009905031,0.00004984766,0.00008327176,0.0002180207,0.003763869,0.0007689991,0.0013285,0.9230768,0.05905767],"study_design_scores_gemma":[0.0002796382,0.00005471498,0.1020279,0.0009118302,0.00005978357,0.0001372183,0.000612699,0.005413166,0.005166054,0.003082454,0.8821213,0.0001332534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001855137,0.00005430319,0.002804737,0.0001823232,0.00004803889,0.000412448,0.9813141,0.001724597,0.01160439],"genre_scores_gemma":[0.01516173,0.0003642214,0.02276178,0.0002256455,0.00003239225,0.003572277,0.9413304,0.001979852,0.01457164],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1657023,"threshold_uncertainty_score":0.5543295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06255200210745517,"score_gpt":0.2116423553053676,"score_spread":0.1490903531979124,"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."}}