{"id":"W4237705041","doi":"10.5194/gmd-2019-220-supplement","title":"Supplementary material to \"COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees\"","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Representation (politics); Tree (set theory); Mathematics; Combinatorics; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006501867,0.001920388,0.001439756,0.001299377,0.0005248529,0.001676228,0.00347353,0.001922978,0.6141973],"category_scores_gemma":[0.004927596,0.001174146,0.001033755,0.002493723,0.0002931947,0.001817112,0.001787176,0.001768662,0.2107565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00072973,"about_ca_system_score_gemma":0.0009658263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01048166,"about_ca_topic_score_gemma":0.00952047,"domain_scores_codex":[0.9996709,0.00005923304,0.00002965492,0.00007703168,0.0001045996,0.00005853849],"domain_scores_gemma":[0.998319,0.0006656763,0.0001118194,0.0002763334,0.0004142198,0.0002128368],"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":[0.00007951233,0.0001025799,0.0005838358,0.000542992,0.00009093929,0.0001282859,0.00003484393,0.01085331,0.0005445582,0.006487491,0.9721081,0.008443501],"study_design_scores_gemma":[0.001552118,0.00009838758,0.004112938,0.0002618919,0.00008289585,0.0003971508,0.00009900135,0.1085929,0.003201751,0.05382991,0.827563,0.0002080346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003059904,0.000327003,0.03209456,0.001095418,0.002746456,0.0001401261,0.9178155,0.01900875,0.02371232],"genre_scores_gemma":[0.03528806,0.0005624039,0.0350984,0.001046536,0.001217819,0.0007195801,0.8715533,0.02941287,0.02510104],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6141973,"threshold_uncertainty_score":0.5503008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01810697346671749,"score_gpt":0.2473544190632594,"score_spread":0.2292474455965419,"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."}}