{"id":"W3012594047","doi":"10.1080/17483107.2020.1741703","title":"Assistive technology use and unmet need in Canada","year":2020,"lang":"en","type":"article","venue":"Disability and Rehabilitation Assistive Technology","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; GF Strong Rehabilitation Centre","funders":"","keywords":"Context (archaeology); Legislation; Population; Government (linguistics); Pace; Sample (material); Needs assessment; Psychology; Environmental health; Medicine; Gerontology; Geography; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007285671,0.0003052345,0.0004043562,0.002439465,0.003326999,0.001501625,0.001333615,0.0004332064,0.004993788],"category_scores_gemma":[0.003591189,0.0002771903,0.0007045131,0.006744718,0.0007678508,0.000549087,0.001456164,0.0007190196,0.0002735787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05058511,"about_ca_system_score_gemma":0.08898977,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9981033,"about_ca_topic_score_gemma":0.9985695,"domain_scores_codex":[0.9985902,0.00005841345,0.0001068506,0.0001232499,0.0006739695,0.0004472191],"domain_scores_gemma":[0.9959955,0.0002140556,0.000421738,0.00005861859,0.002300538,0.001009498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000880129,0.00006534778,0.9506117,0.0005377195,0.00009418852,0.0002482882,0.003498345,0.0002884016,0.0001453415,0.0007340045,0.01291787,0.03077086],"study_design_scores_gemma":[0.00001313283,0.00002883828,0.987387,0.000293515,0.00004021022,0.0001392142,0.004815761,0.0006097123,0.00007796047,0.0001578723,0.006402595,0.00003405094],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9335234,0.005203997,0.0003113739,0.005251156,0.00009650376,0.0002185712,0.03279723,0.00006036667,0.02253742],"genre_scores_gemma":[0.9910564,0.002159284,0.0003797402,0.0004858566,0.00001110917,0.00006284643,0.003886807,0.000009537,0.001948365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05058511,"threshold_uncertainty_score":0.3670223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160851924524039,"score_gpt":0.356179637899674,"score_spread":0.3145711186544336,"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."}}