{"id":"W4211239937","doi":"10.32866/001c.32444","title":"Cumulative versus Gravity-based Accessibility Measures: Which One to Use?","year":2022,"lang":"en","type":"article","venue":"Findings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Sydney; University of Twente; McMaster University","keywords":"Operationalization; Metropolitan area; Public transport; Gravity model of trade; Econometrics; Cumulative distribution function; Cumulative effects; Computer science; Transport engineering; Mathematics; Statistics; Economics; Geography; Engineering; Physics; Probability density function","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001819751,0.0001485521,0.0002351482,0.0001257647,0.001792511,0.000226004,0.0006694171,0.00007483961,0.001858111],"category_scores_gemma":[0.0008118961,0.0001657057,0.0001098441,0.001523341,0.0001375595,0.0005046307,0.0001103748,0.0003581737,0.00004219978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005311611,"about_ca_system_score_gemma":0.0004510118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006527601,"about_ca_topic_score_gemma":0.01198121,"domain_scores_codex":[0.997241,0.0003178072,0.0002886413,0.0005649871,0.001104887,0.0004827166],"domain_scores_gemma":[0.9987292,0.0003702214,0.00008984116,0.0003552123,0.000211721,0.0002437771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007185768,0.0003402516,0.9808302,0.00001442421,0.00002915448,0.000004550469,0.01374876,0.0001409085,0.0002522496,0.002029315,0.001102596,0.0007890175],"study_design_scores_gemma":[0.001167834,0.00017712,0.9115602,0.00001477175,0.00004956383,2.666489e-8,0.001861616,0.00003638296,0.0005306856,0.002070956,0.08212471,0.0004060699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912896,0.00001184916,0.0003584144,0.001744432,0.0006682013,0.0005347088,0.0001172431,0.0001659249,0.005109698],"genre_scores_gemma":[0.9981009,5.604768e-7,0.0004642688,0.0003575387,0.00009483736,0.00008602428,0.0000459609,0.0000150721,0.0008348268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08102211,"threshold_uncertainty_score":0.999507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.106124895673224,"score_gpt":0.3512466756179042,"score_spread":0.2451217799446802,"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."}}