{"id":"W2101371478","doi":"10.1068/a34171","title":"Measuring Neighbourhood Spatial Accessibility to Urban Amenities: Does Aggregation Error Matter?","year":2002,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":249,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Neighbourhood (mathematics); Amenity; Computer science; Recreation; Data aggregator; Geography; Econometrics; Business; Economics; Political science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003000885,0.0001358091,0.0001663278,0.00004654688,0.0005176378,0.0001800647,0.00009845438,0.00007357101,0.001778892],"category_scores_gemma":[0.00001366253,0.0001190526,0.00003049467,0.00003571777,0.0001597,0.0004267775,0.00003281027,0.0001035277,0.00004053352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005687114,"about_ca_system_score_gemma":0.000007715914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009727844,"about_ca_topic_score_gemma":0.0003291931,"domain_scores_codex":[0.9990367,0.00006223074,0.0001778685,0.0003630449,0.0001043219,0.0002558237],"domain_scores_gemma":[0.9995375,0.00006487619,0.00007613804,0.0001310588,0.00000512343,0.0001853626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001452127,0.00002746006,0.9744694,0.00001705408,0.00001021152,0.000002520353,0.02069926,0.00002007217,0.00000934492,0.00006628435,0.0001876379,0.004476251],"study_design_scores_gemma":[0.0003445551,0.00004249518,0.9487662,0.00005480061,0.00002761554,3.686426e-7,0.005598769,0.0003731862,0.000162439,0.0007795585,0.04350907,0.0003409349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787704,0.0004477686,0.0006892176,0.001782391,0.00009506715,0.0002333712,0.000009020176,0.00003241082,0.01794039],"genre_scores_gemma":[0.9969935,0.00004710814,0.0002164912,0.0002321349,0.0002347414,0.00001810122,0.000004456497,0.000007093046,0.002246416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04332143,"threshold_uncertainty_score":0.9991336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03143880229902658,"score_gpt":0.237685809231875,"score_spread":0.2062470069328484,"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."}}