{"id":"W2080238278","doi":"10.1016/s0093-934x(03)00419-x","title":"What does rapid automatized naming measure? A new RAN task compared to naming and lexical decision","year":2004,"lang":"en","type":"article","venue":"Brain and Language","topic":"Reading and Literacy Development","field":"Psychology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lexical decision task; Rapid automatized naming; Psychology; Ran; Vocabulary; Latency (audio); Word recognition; Cognitive psychology; Reading (process); Linguistics; Cognition; Phonological awareness; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0004327621,0.0001672818,0.0002614555,0.0001338792,0.000121105,0.0002318695,0.00009828197,0.00008507131,0.0002057353],"category_scores_gemma":[0.0001746358,0.0001209556,0.00003735198,0.0001317741,0.00003513582,0.0001469988,0.00005402905,0.0001162409,0.00004558863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003323046,"about_ca_system_score_gemma":0.00002886738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002924133,"about_ca_topic_score_gemma":0.0001370754,"domain_scores_codex":[0.9988465,0.00008165862,0.0002475184,0.0003709432,0.000174271,0.0002791552],"domain_scores_gemma":[0.9991701,0.0003130637,0.00004530442,0.0002063994,0.00001504306,0.000250097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000281437,0.00006356796,0.0003318801,0.00002822082,0.00006599391,0.0001490994,0.2402881,0.000003223123,0.008315104,0.001462429,0.003838405,0.7451726],"study_design_scores_gemma":[0.05464758,0.0008947001,0.3490665,0.008154987,0.0001886715,0.001519168,0.2375833,0.0007448551,0.005282471,0.006261308,0.331631,0.004025546],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878455,0.003040621,0.004537723,0.002435255,0.0005784267,0.0002631655,0.0000035568,0.0001213113,0.001174387],"genre_scores_gemma":[0.9861144,0.00002415084,0.008936643,0.00219252,0.0001278577,0.00001481042,0.00001215043,0.00002060245,0.002556802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.741147,"threshold_uncertainty_score":0.4932427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357458616665441,"score_gpt":0.3077182634683761,"score_spread":0.2941436773017216,"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."}}