{"id":"W7015732951","doi":"","title":"Using Google Earth and Census Data to Explore your City's Spatial Structure, Demonstration (20 min)","year":2021,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Population; Neighbourhood (mathematics); American Community Survey; Data collection; Spatial analysis","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":[0.0008307074,0.001236239,0.000594852,0.003143399,0.00189502,0.001676423,0.001045624,0.0008007403,0.1885304],"category_scores_gemma":[0.007083179,0.000638222,0.0009892884,0.005450205,0.0004925177,0.002205603,0.002820594,0.00104138,0.08112858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00076402,"about_ca_system_score_gemma":0.001647451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09211703,"about_ca_topic_score_gemma":0.2800939,"domain_scores_codex":[0.9996086,0.00005666978,0.00002780762,0.00006390134,0.000182294,0.00006074657],"domain_scores_gemma":[0.9975933,0.0007996081,0.00009692011,0.0003667517,0.000829259,0.0003140759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002788863,0.00002487575,0.0005746975,0.0002115688,0.000008595297,0.0001139884,0.0009087452,0.0001005914,0.0003266488,0.0004582869,0.9654968,0.03174723],"study_design_scores_gemma":[0.0001053105,0.00004416955,0.01192819,0.000191366,0.00001918004,0.0001702046,0.003069336,0.0009173929,0.0006559542,0.002453207,0.9803633,0.00008239424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.02352117,0.001579401,0.03596225,0.01372664,0.002740549,0.004057754,0.5582197,0.06684771,0.2933448],"genre_scores_gemma":[0.1153291,0.003996803,0.2503567,0.00473986,0.001481415,0.011246,0.2616476,0.0181597,0.3330427],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1885304,"threshold_uncertainty_score":0.6306969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3757463777350183,"score_gpt":0.3878648352009906,"score_spread":0.01211845746597234,"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."}}