{"id":"W4206092104","doi":"10.1016/j.trip.2021.100533","title":"Accessing hemodialysis clinics during the COVID-19 pandemic","year":2022,"lang":"en","type":"article","venue":"Transportation Research Interdisciplinary Perspectives","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Hôpital Maisonneuve-Rosemont; Université de Montréal; Centre Hospitalier de l’Université de Montréal; McGill University","funders":"Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Ministère de la Santé et des Services sociaux","keywords":"Paratransit; Pandemic; Public transport; Descriptive statistics; Hemodialysis; Taxis; Coronavirus disease 2019 (COVID-19); Thematic analysis; Medical emergency; Medicine; Business; Psychology; Transport engineering; Engineering; Sociology; Qualitative research; Disease; Surgery; Statistics; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001760187,0.0001195527,0.0002163499,0.0002370092,0.002313655,0.001333461,0.000469697,0.0006366228,0.002350098],"category_scores_gemma":[0.007104193,0.0001386511,0.0003117266,0.000304314,0.0008702795,0.0009428342,0.001315519,0.0009814024,0.0001259454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00303498,"about_ca_system_score_gemma":0.003676007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0447747,"about_ca_topic_score_gemma":0.08886111,"domain_scores_codex":[0.9983175,0.000754948,0.00009802647,0.0001016283,0.000266698,0.0004612282],"domain_scores_gemma":[0.9958969,0.001252661,0.00131239,0.00008674627,0.0004066703,0.001044701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00024761,0.000250147,0.8186567,0.0004178409,0.0001056569,0.0025475,0.1103841,0.0003212983,0.001785398,0.001019136,0.009411031,0.05485361],"study_design_scores_gemma":[0.00002346581,0.0003995539,0.7047397,0.0005142204,0.00006456018,0.001931316,0.2735355,0.0005254849,0.0004266697,0.0006752618,0.01708571,0.00007851628],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918827,0.0006502729,0.0003442687,0.003432173,0.00004636188,0.00004232625,0.0001042159,0.00001650904,0.003481178],"genre_scores_gemma":[0.9977648,0.0005340147,0.0002316238,0.001085373,0.00002992132,0.00001667677,0.00003900158,0.000002830961,0.000295638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0447747,"threshold_uncertainty_score":0.08902818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2306750792098312,"score_gpt":0.5580811009308707,"score_spread":0.3274060217210395,"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."}}