{"id":"W3124070564","doi":"10.20561/00037625","title":"THE IMPACT OF A COMPUTER BASED ADULT LITERACY PROGRAM ON LITERACY AND NUMERACY-EVIDENCE FROM INDIA","year":2016,"lang":"en","type":"preprint","venue":"Institutional Repositories DataBase (IRDB)","topic":"ICT in Developing Communities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Numeracy; Literacy; Adult literacy; Standardization; Computer literacy; Mathematics education; Medical education; Computer science; Psychology; Pedagogy; Medicine","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":[0.004069834,0.0003189353,0.0007190597,0.001132423,0.0003901449,0.001138399,0.0007224239,0.0004953293,0.004790491],"category_scores_gemma":[0.01952777,0.0001627645,0.001210472,0.002139319,0.001240043,0.0005759257,0.0009339311,0.001069173,0.0003187529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109112,"about_ca_system_score_gemma":0.002905364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01241301,"about_ca_topic_score_gemma":0.01468747,"domain_scores_codex":[0.9948703,0.003153437,0.0005882732,0.0002372898,0.0008507632,0.0002999461],"domain_scores_gemma":[0.9786369,0.01537514,0.003065075,0.0007812949,0.001087962,0.001053641],"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":[0.05683064,0.01837341,0.07267042,0.03862171,0.005520255,0.000405814,0.002650276,0.001250896,0.001827459,0.002685418,0.004130945,0.7950328],"study_design_scores_gemma":[0.03291408,0.1153027,0.7513843,0.02811488,0.02959481,0.0007561693,0.003698575,0.001066197,0.006570439,0.002065615,0.02838314,0.0001489588],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9347312,0.03842118,0.0004303976,0.003431699,0.0002678393,0.001257067,0.00119283,0.00008267338,0.02018507],"genre_scores_gemma":[0.9810516,0.01614913,0.0007500628,0.0007723248,0.00009060228,0.0003004297,0.0002743762,0.0000125202,0.0005988777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01241301,"threshold_uncertainty_score":0.02468151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02305482791023062,"score_gpt":0.3255042606151838,"score_spread":0.3024494327049532,"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."}}