{"id":"W7055978996","doi":"","title":"Do hours spent watching television at age 3 and 4 predict vocabulary and executive functioning at age 5?","year":2015,"lang":"en","type":"other","venue":"NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health; York University","keywords":"Vocabulary; Context (archaeology); Association (psychology); Vocabulary development; Age groups; Vocabulary learning","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":[0.0008874899,0.0004494525,0.0002801736,0.000965985,0.0004544589,0.001142966,0.0005824061,0.0009663145,0.001940799],"category_scores_gemma":[0.002644899,0.0002889853,0.000842444,0.000462727,0.0003297529,0.0006487401,0.0006282248,0.0007847018,0.000627209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005877368,"about_ca_system_score_gemma":0.0004893934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02444115,"about_ca_topic_score_gemma":0.0509335,"domain_scores_codex":[0.9997529,0.00003391303,0.00002226743,0.00006044794,0.00005291065,0.00007752215],"domain_scores_gemma":[0.9974914,0.0003308453,0.001259246,0.0001553552,0.0002664224,0.0004966988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006097689,0.0000876919,0.9971227,0.000006375151,0.00002476171,0.0001141609,0.0003664637,0.00002884269,0.0001844795,0.00002333197,0.000101784,0.001878537],"study_design_scores_gemma":[9.244242e-7,0.00005739793,0.9993916,0.000007227342,0.00001103305,0.00004893705,0.0002789447,0.00002899198,0.00006998594,0.00001760206,0.00008551117,0.000001886248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991444,0.0001597529,0.00002174247,0.00002947623,0.000004365469,0.000002913025,0.0001841167,0.000002497162,0.0004507185],"genre_scores_gemma":[0.9982286,0.0001500163,0.0001161707,0.0000275423,0.000004967072,0.000009756845,0.0005930625,0.000001986102,0.0008677992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02444115,"threshold_uncertainty_score":0.04859775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636636667989467,"score_gpt":0.2105481701817828,"score_spread":0.1941818035018881,"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."}}