{"id":"W4416353039","doi":"10.2139/ssrn.5767066","title":"Lessons in AI Literacy and Explainability from Lucy and Ricky","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Literacy; sort; Adult literacy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002449648,0.0003695713,0.0004967432,0.0004191686,0.000269034,0.000940721,0.001293077,0.0002916153,0.000007452335],"category_scores_gemma":[0.0003029326,0.0003687103,0.0001072884,0.0003852888,0.0001140373,0.0009654727,0.001755681,0.005470272,0.000005874039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297,"about_ca_system_score_gemma":0.003831231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002340371,"about_ca_topic_score_gemma":0.003970112,"domain_scores_codex":[0.9956216,0.0003762334,0.0006533207,0.0009763484,0.0003096642,0.002062784],"domain_scores_gemma":[0.9982741,0.0003462548,0.0002588852,0.0007704873,0.0001938355,0.0001564385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003859646,0.0001684775,0.006834614,0.00006469973,0.0001006362,0.00004918062,0.004942036,0.0002969722,0.00005566581,0.7399296,0.00004627077,0.2474733],"study_design_scores_gemma":[0.0001890583,0.00009710884,0.002494243,0.0002063465,0.00001808953,0.0000789093,0.0005856911,0.01515267,0.0002738253,0.980021,0.0005518971,0.0003311521],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4584948,0.01993759,0.5006537,0.01898042,0.0007644028,0.0004752733,0.0000180048,0.00009810591,0.0005777225],"genre_scores_gemma":[0.9864274,0.00937369,0.003251717,0.0003075783,0.000170541,0.00002991749,0.000004134933,0.00001346439,0.0004215798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5279326,"threshold_uncertainty_score":0.9998765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416387573049721,"score_gpt":0.3116542392430538,"score_spread":0.2974903635125566,"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."}}