{"id":"W1515448078","doi":"10.5539/gjhs.v8n1p36","title":"Model of Providing Assistive Technologies in Special Education Schools","year":2015,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"Chiang Mai University","keywords":"Checklist; Assistive technology; Nonprobability sampling; Special education; Medical education; Psychology; Independent living; Government (linguistics); Pedagogy; Medicine; Gerontology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005894816,0.00008001579,0.0003136451,0.0002981533,0.000325248,0.000005935086,0.0009310817,0.0001210505,0.00000349713],"category_scores_gemma":[0.002899808,0.00006531782,0.00003136547,0.001110507,0.0006361025,0.0003529595,0.0002898505,0.0007642957,0.0000071508],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002259758,"about_ca_system_score_gemma":0.02034499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001120142,"about_ca_topic_score_gemma":0.0001015488,"domain_scores_codex":[0.99778,0.0002049398,0.001046212,0.0001567532,0.0004626049,0.000349467],"domain_scores_gemma":[0.9967461,0.00006275689,0.001400831,0.0003571915,0.001303469,0.0001296265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006312853,0.0001947784,0.9278172,0.00004381676,0.000002295167,3.99122e-7,0.0002988661,0.00009455783,0.0001076252,0.01583875,0.004225693,0.05131292],"study_design_scores_gemma":[0.001416384,0.0004996976,0.847701,0.001241331,0.000008736783,0.00003347698,0.07696663,0.001833348,0.00019659,0.0679409,0.001974847,0.0001870256],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630886,0.001137401,0.004555712,0.01760317,0.001273882,0.000690377,0.00001262185,0.00006397477,0.01157424],"genre_scores_gemma":[0.980475,0.00008282498,0.01914879,0.0002107754,0.00004992398,0.00001250567,3.310283e-7,0.000002164413,0.00001766617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08011613,"threshold_uncertainty_score":0.9852087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1807009933070754,"score_gpt":0.5009158525420672,"score_spread":0.3202148592349917,"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."}}