{"id":"W2992268601","doi":"","title":"Smart eco-path finder for mobile GIS users","year":2013,"lang":"en","type":"article","venue":"Journal of the Urban and Regional Information Systems Association","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Walkability; Signage; Destinations; Built environment; Computer science; Transport engineering; Quality (philosophy); Geography; Business; Engineering; Advertising; Civil engineering","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":[0.0008255144,0.001402102,0.0009373472,0.001974131,0.0003661861,0.001581793,0.001565108,0.0009719159,0.1578312],"category_scores_gemma":[0.004641165,0.0004111947,0.0007043321,0.001727269,0.0002044299,0.00241761,0.002097144,0.0007349068,0.0785301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003350702,"about_ca_system_score_gemma":0.0005105301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002381597,"about_ca_topic_score_gemma":0.003559093,"domain_scores_codex":[0.9995871,0.00005611914,0.00003506739,0.000116023,0.0001554164,0.00005030689],"domain_scores_gemma":[0.9979196,0.0006234826,0.0001692725,0.0004823596,0.0005922881,0.0002129153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001014375,0.0001715617,0.008539846,0.001195297,0.00007030959,0.0004799152,0.0009313953,0.001087544,0.005573187,0.004022849,0.5611995,0.4157142],"study_design_scores_gemma":[0.0003456174,0.0003262001,0.02515541,0.0006197201,0.0001573584,0.001172766,0.001246091,0.02347875,0.01174266,0.01723463,0.9182586,0.0002622917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.03604534,0.001659308,0.117287,0.002086251,0.0007284263,0.001778544,0.2505443,0.4395727,0.1502982],"genre_scores_gemma":[0.2964497,0.002613982,0.3253507,0.00223674,0.0006548321,0.005891896,0.1710632,0.02858369,0.1671552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1578312,"threshold_uncertainty_score":0.527998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705900777755371,"score_gpt":0.2538254510729838,"score_spread":0.2367664432954301,"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."}}