{"id":"W2966036445","doi":"","title":"Functional and structural neural contributions to skilled word reading","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Neuroscience, Education and Cognitive Function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reading (process); Word (group theory); Computer science; Linguistics; Psychology; Natural language processing; Artificial intelligence; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002037354,0.0002326338,0.0001503734,0.0002346946,0.0001388347,0.0003866557,0.0002061927,0.0003940007,0.003845737],"category_scores_gemma":[0.001139331,0.0002412061,0.0001762043,0.0001387169,0.000480022,0.0005274281,0.0003236848,0.000469655,0.0002396567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001727922,"about_ca_system_score_gemma":0.0001849614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099338,"about_ca_topic_score_gemma":0.002107572,"domain_scores_codex":[0.9999288,0.000008346908,0.000003574355,0.00003185618,0.00001310764,0.00001425697],"domain_scores_gemma":[0.9997082,0.0001590137,0.00006232229,0.00002513758,0.00002090093,0.00002437441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001151394,0.0002477595,0.02583637,0.0003455523,0.0001002985,0.000654043,0.002168566,0.001169491,0.9025766,0.00346965,0.0005948659,0.06168542],"study_design_scores_gemma":[0.0001146099,0.001304936,0.9390517,0.00005433673,0.0001542354,0.001987897,0.0009021151,0.004734674,0.04274697,0.007489328,0.001425428,0.00003378191],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956031,0.0002275754,0.001645502,0.0001124187,0.00000794877,0.00002401633,0.0001513064,0.00003459179,0.002193675],"genre_scores_gemma":[0.9964426,0.0002787777,0.001592279,0.00004712641,0.00001257657,0.00004159816,0.0001547954,0.00001661992,0.001413548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003845737,"threshold_uncertainty_score":0.0128653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124014235154953,"score_gpt":0.3136858282649642,"score_spread":0.2924456859134147,"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."}}