{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004600593,0.000349173,0.0006696299,0.00147122,0.00142118,0.003719579,0.0008301645,0.002341659,0.01115836],"category_scores_gemma":[0.02817981,0.000392027,0.0004164258,0.001274277,0.01568428,0.01835291,0.002557571,0.005038659,0.001078265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001948475,"about_ca_system_score_gemma":0.001370323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004516297,"about_ca_topic_score_gemma":0.002364559,"domain_scores_codex":[0.9980762,0.00112317,0.00009974403,0.0002877502,0.0003105692,0.0001026815],"domain_scores_gemma":[0.9722936,0.0235368,0.0007043891,0.001738007,0.001331074,0.0003961768],"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":[0.00003340321,0.00003884837,0.001277894,0.00008806148,0.00001390944,0.00008718589,0.004785843,0.000423656,0.00007223837,0.9700613,0.005656388,0.01746117],"study_design_scores_gemma":[0.0000151684,0.000006647498,0.0005892937,0.00005119127,0.00000382441,0.00005284427,0.0006073426,0.0005000657,0.0001091341,0.9845345,0.01352228,0.000007736764],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1374297,0.03142429,0.09358428,0.4107858,0.0008525684,0.00006440276,0.0002842533,0.0002486854,0.325326],"genre_scores_gemma":[0.9595568,0.005162813,0.0119909,0.007536925,0.0008669264,0.00007393801,0.0001157211,0.0001665957,0.01452939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01115836,"threshold_uncertainty_score":0.03732836,"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."}}