{"id":"W4324376641","doi":"10.3389/fresc.2023.1023582","title":"WalkRollMap.org: Crowdsourcing barriers to mobility","year":2023,"lang":"en","type":"article","venue":"Frontiers in Rehabilitation Sciences","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; University of Saskatchewan; Simon Fraser University; University of Victoria","funders":"Canadian Institutes of Health Research; Public Health Agency; Public Health Agency of Canada; University of Victoria","keywords":"Crowdsourcing; Pedestrian; Outreach; Variety (cybernetics); Data science; Scale (ratio); Computer science; Internet privacy; Transport engineering; World Wide Web; Engineering; Geography; Political science; Cartography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002822464,0.001349612,0.0007195049,0.003864615,0.001346455,0.002141712,0.001777729,0.00133597,0.02323904],"category_scores_gemma":[0.01089766,0.0004819891,0.001298825,0.002695906,0.0004762643,0.002142607,0.006134934,0.001281727,0.01349096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000777764,"about_ca_system_score_gemma":0.001748263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01969636,"about_ca_topic_score_gemma":0.03177968,"domain_scores_codex":[0.9978714,0.0004533884,0.0001261117,0.0003632334,0.0009502513,0.0002356756],"domain_scores_gemma":[0.9943163,0.002178167,0.0003887785,0.001274857,0.001129021,0.0007128823],"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":[0.000583121,0.0002294725,0.01636152,0.002024797,0.0002543112,0.0003602678,0.005041842,0.006147451,0.004057931,0.006756051,0.7629607,0.1952225],"study_design_scores_gemma":[0.0003278479,0.0002252475,0.02816233,0.0008177339,0.0001369733,0.0001489899,0.004933237,0.03386611,0.004718946,0.02267676,0.9036014,0.0003843908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.05520497,0.001472812,0.1339247,0.005885073,0.003386188,0.004204833,0.4933152,0.1521255,0.1504808],"genre_scores_gemma":[0.3663184,0.00141932,0.199332,0.002985999,0.0008662867,0.009233805,0.3347633,0.02162946,0.06345134],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02323904,"threshold_uncertainty_score":0.07774234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543969159078854,"score_gpt":0.3374237762800819,"score_spread":0.3119840846892934,"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."}}