{"id":"W4401726575","doi":"10.1177/23998083241276021","title":"Spnaf: An R package for analyzing and mapping the hotspots of flow datasets","year":2024,"lang":"en","type":"article","venue":"Environment and Planning B Urban Analytics and City Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"R package; Computer science; Hotspot (geology); Spatial analysis; Data mining; Shapefile; Database; Cartography; Geography; World Wide Web; Remote sensing; Metadata","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006341631,0.003381909,0.0026927,0.004590258,0.0007834794,0.00323586,0.003742161,0.001175875,0.06629711],"category_scores_gemma":[0.04462453,0.001906408,0.003398671,0.004501558,0.0009701401,0.002487212,0.003275729,0.003330421,0.04287361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008055065,"about_ca_system_score_gemma":0.003629525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007870628,"about_ca_topic_score_gemma":0.009917133,"domain_scores_codex":[0.9960473,0.00162722,0.0003753385,0.0009299692,0.0007802344,0.0002399529],"domain_scores_gemma":[0.9814817,0.01347815,0.001239861,0.00212257,0.001315086,0.0003626394],"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":[0.0002879852,0.00005457335,0.01138091,0.002085285,0.001498655,0.0003509306,0.000418172,0.01345948,0.001430274,0.01168509,0.8930603,0.06428837],"study_design_scores_gemma":[0.0007208587,0.0001599156,0.01677011,0.0007332815,0.0007603464,0.0007828726,0.0002051294,0.06079422,0.004952306,0.06668177,0.8470731,0.000366245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00451351,0.000892089,0.367717,0.0009605839,0.0004883352,0.0004644904,0.3814054,0.2380682,0.005490461],"genre_scores_gemma":[0.04603151,0.001047335,0.4746747,0.001605463,0.0003783651,0.006547406,0.2939066,0.1690731,0.006735567],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06629711,"threshold_uncertainty_score":0.221786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05233552773680944,"score_gpt":0.2969273884086829,"score_spread":0.2445918606718735,"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."}}