{"id":"W4244523250","doi":"10.31234/osf.io/9vquy","title":"Insights from a dyslexia simulation font: Can we simulate reading struggles of individuals with dyslexia","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Reading and Literacy Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MAB-Mackay Rehabilitation Centre; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Concordia University","funders":"","keywords":"Dyslexia; Reading (process); Font; Psychology; Cognitive psychology; Perception; Computer science; Linguistics; Artificial intelligence; Neuroscience","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":[0.001128538,0.0002948185,0.0002426216,0.0003862534,0.0003346941,0.001408719,0.0003995702,0.0007524209,0.001657828],"category_scores_gemma":[0.00866982,0.0001508519,0.000276961,0.0001715328,0.001157574,0.001467434,0.001094493,0.0005881363,0.0002893548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004534999,"about_ca_system_score_gemma":0.0003132758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00109824,"about_ca_topic_score_gemma":0.002153458,"domain_scores_codex":[0.9991283,0.0006052241,0.00004636219,0.00009847737,0.00007806831,0.00004371849],"domain_scores_gemma":[0.9946902,0.004054838,0.0003896278,0.0003710451,0.0002248733,0.0002694961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001800254,0.00264877,0.2527218,0.0009843342,0.0001480921,0.009403934,0.5146115,0.009745478,0.0682096,0.01521757,0.008011614,0.116497],"study_design_scores_gemma":[0.0005036122,0.007932701,0.4851629,0.0006767223,0.000291406,0.01638545,0.289436,0.04415075,0.02995172,0.04867696,0.07647233,0.0003595072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931747,0.00006976043,0.001991638,0.0005754737,0.00001091681,0.00002494355,0.00006222487,0.00004481693,0.004045541],"genre_scores_gemma":[0.9959941,0.00009048732,0.00286045,0.0001410555,0.000003979115,0.00003183308,0.00007344475,0.00001683394,0.0007877454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001657828,"threshold_uncertainty_score":0.005968332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03993348630191726,"score_gpt":0.3196136940919613,"score_spread":0.2796802077900441,"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."}}