{"id":"W4400313023","doi":"10.2139/ssrn.4885628","title":"Spatial Representativeness of Weather Stations and Their Impact on Urban Climate Research: A Case Study of the Uhi in Canada","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Representativeness heuristic; Urban heat island; Geography; Urban climate; Environmental science; Climatology; Meteorology; Climate change; Environmental resource management; Urban planning; Civil engineering; Engineering; Geology; Oceanography; Statistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00214613,0.0001958272,0.0003815626,0.001355463,0.002583466,0.002685657,0.001047347,0.0005273278,0.001226981],"category_scores_gemma":[0.009290488,0.0002105632,0.0003345725,0.007260354,0.00171301,0.0007077961,0.001073955,0.0004594062,0.00006661182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02024276,"about_ca_system_score_gemma":0.02506002,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.992436,"about_ca_topic_score_gemma":0.9951152,"domain_scores_codex":[0.9985525,0.000358859,0.00006487277,0.000165548,0.0004710437,0.0003871235],"domain_scores_gemma":[0.9940026,0.002524737,0.0005804593,0.0003206391,0.002141141,0.0004302914],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002474816,0.00009066191,0.9098709,0.0001843032,0.0002143313,0.0008563081,0.006624865,0.03072476,0.001119054,0.005306526,0.002374398,0.04238643],"study_design_scores_gemma":[0.00001540313,0.00003693684,0.9558997,0.000056402,0.00009905715,0.0001184219,0.01862385,0.01782406,0.0005123258,0.0008044543,0.005964794,0.00004452703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924278,0.0005279338,0.0005187502,0.0007376798,0.000005955053,0.00002856807,0.001060481,0.00001736097,0.004675464],"genre_scores_gemma":[0.9984252,0.0002748382,0.0004850218,0.00002161972,0.000002665792,0.000005178829,0.0002261835,0.000004302295,0.0005550592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9978539,"threshold_uncertainty_score":0.1468722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028680562864519,"score_gpt":0.3166666849234477,"score_spread":0.2879861220589287,"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."}}