{"id":"W2540081459","doi":"10.1002/joc.4887","title":"Accessing vulnerability of land‐cover types to climate change using physical scaling downscaling model","year":2016,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Aeronautics and Space Administration","keywords":"Downscaling; Land cover; Environmental science; Moderate-resolution imaging spectroradiometer; Climatology; Climate change; Scale (ratio); Representative Concentration Pathways; Climate model; Vulnerability (computing); Land use; Physical geography; Geography; Satellite; Geology; Computer science; Cartography","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":[0.000339735,0.00008548324,0.000222529,0.00008920356,0.00003398837,0.00001542446,0.0002793028,0.00005015329,0.0001641327],"category_scores_gemma":[0.0001476521,0.00005774265,0.00009115865,0.00006778523,0.00009163706,0.0004654894,0.0001614122,0.00008329251,0.0000379925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000155824,"about_ca_system_score_gemma":0.00001657556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003023209,"about_ca_topic_score_gemma":0.000009293194,"domain_scores_codex":[0.9988586,0.0000614422,0.0004141527,0.0001352209,0.0003564426,0.0001741268],"domain_scores_gemma":[0.9992922,0.0001493025,0.000307161,0.00008651789,0.0000942706,0.00007052795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003338909,0.0001842999,0.79877,0.00001342049,0.00005432824,0.00002304774,0.001052141,0.03094919,0.1467428,0.0006238191,0.00005323971,0.02119987],"study_design_scores_gemma":[0.00576069,0.0004881317,0.2209762,0.001592602,0.000279581,0.001321117,0.0001111375,0.5603256,0.174396,0.0327638,0.0009745948,0.001010561],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824826,0.00001478397,0.01576222,0.0008954086,0.0003427692,0.0000568051,0.00001853154,0.000005833434,0.000421048],"genre_scores_gemma":[0.9954309,0.00001766114,0.004158721,0.0001834926,0.0001926286,0.000001606606,7.563498e-7,0.00000869546,0.000005507272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5777938,"threshold_uncertainty_score":0.2354677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846995473899659,"score_gpt":0.3417718092838245,"score_spread":0.2933018545448279,"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."}}