{"id":"W4255718332","doi":"10.32920/14636943.v1","title":"Toronto’s Urban Heat Island : Exploring the Relationship between Land Use and Surface Temperature","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Resources Canada","keywords":"Urban heat island; Recreation; Resource (disambiguation); Environmental science; Geography; Land use; Order (exchange); Physical geography; Natural resource economics; Meteorology; Business; Economics; Ecology; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002774316,0.0002488605,0.0002255028,0.000009262954,0.0002596009,0.0004315528,0.0001914285,0.0002242655,0.0006183559],"category_scores_gemma":[0.0001350466,0.0001723448,0.00006175413,0.00007571312,0.00009832587,0.0006886458,0.0007084657,0.0005526989,0.00002623182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002531012,"about_ca_system_score_gemma":0.00002295553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01177984,"about_ca_topic_score_gemma":0.02487963,"domain_scores_codex":[0.9985165,0.0001740577,0.0002389288,0.0005353355,0.0002997947,0.0002354042],"domain_scores_gemma":[0.998796,0.0004897809,0.00004212831,0.0005533544,0.00001245798,0.0001062239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002233523,0.000007518995,0.9926963,0.00001770564,0.00001565888,0.000002654342,0.001855477,0.0005841972,0.0002339912,0.00002348991,0.004508183,0.00005259073],"study_design_scores_gemma":[0.0001401634,0.00001228894,0.9977955,0.00007016514,0.00004801126,0.000004302322,0.0002541459,0.00008038851,0.0002977196,0.0001306184,0.0009310822,0.0002356275],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960162,0.0005241557,0.00007048745,0.000492793,0.0002633513,0.0003938647,0.00004554168,0.00006142483,0.002132153],"genre_scores_gemma":[0.9946672,0.0001377023,0.0005660424,0.00008621346,0.0001767161,0.00003382923,0.000177911,0.00002505471,0.00412933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01309979,"threshold_uncertainty_score":0.9948008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06672229515307286,"score_gpt":0.2443212973410692,"score_spread":0.1775990021879963,"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."}}