{"id":"W4404181996","doi":"10.1080/15512169.2024.2426153","title":"Navigating Generative AI Tools in the Classroom Through a Lens of Equity and Accessibility","year":2024,"lang":"en","type":"article","venue":"Journal of Political Science Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Equity (law); Generative grammar; Through-the-lens metering; Lens (geology); Psychology; Mathematics education; Political science; Computer science; Artificial intelligence; Engineering; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.00252794,0.00005056012,0.0001242559,0.00005454526,0.00008457738,0.0001252251,0.0001364654,0.00003903151,0.00001854106],"category_scores_gemma":[0.002456151,0.00003025418,0.00003596416,0.0005575639,0.0004369226,0.000913661,0.00003338328,0.000409817,0.0000013564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003366177,"about_ca_system_score_gemma":0.004106557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007612282,"about_ca_topic_score_gemma":0.00003869362,"domain_scores_codex":[0.9986356,0.00007517445,0.0004952589,0.0001237465,0.0004245726,0.0002455853],"domain_scores_gemma":[0.9988092,0.0004270733,0.00009616687,0.0001054644,0.000447304,0.0001148562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003707943,0.0005487881,0.06738333,0.0003253311,0.000007092419,0.000004788344,0.02760957,0.000003951538,0.01298709,0.5372289,0.0003994204,0.3534647],"study_design_scores_gemma":[0.00005296312,0.0007235145,0.5017247,0.001570723,0.00006287587,0.0003514157,0.05418943,0.001390394,0.05851797,0.380855,0.0004499606,0.0001110162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9354862,0.0003315767,0.0005326532,0.06217168,0.0005828099,0.0001303148,0.000001307646,0.000002411666,0.0007610234],"genre_scores_gemma":[0.9958223,0.00002902079,0.001010733,0.002538084,0.000587574,0.000003147724,7.031384e-7,0.000002143946,0.000006348536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4343414,"threshold_uncertainty_score":0.7284855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3075170966289069,"score_gpt":0.5775122985779967,"score_spread":0.2699952019490898,"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."}}