{"id":"W7116738429","doi":"10.33137/jns.v4i1.43776","title":"Unlocking the Future: Exploring Generative Artificial Intelligence in Post-Secondary Chemistry Education with a Focus on Summative Assessment Applications","year":2025,"lang":"","type":"article","venue":"UTSC s Journal of Natural Sciences","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Summative assessment; Leverage (statistics); Generative grammar; Theme (computing); Formative assessment; Applications of artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.03477191,0.0006816345,0.001099113,0.006458369,0.001132403,0.00742729,0.001336505,0.001298065,0.002787848],"category_scores_gemma":[0.06535772,0.0003499679,0.001244821,0.005574887,0.002704979,0.007175194,0.003480382,0.001833007,0.0005472445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003092378,"about_ca_system_score_gemma":0.009343965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600482,"about_ca_topic_score_gemma":0.00606272,"domain_scores_codex":[0.9764365,0.01706343,0.001697162,0.0007442478,0.003686007,0.0003726534],"domain_scores_gemma":[0.8871701,0.1005687,0.003614692,0.001641723,0.00630035,0.0007044132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001131187,0.0001253159,0.002885252,0.09800881,0.0004096517,0.000491578,0.05639978,0.0005897285,0.001623534,0.01986768,0.004945362,0.8145402],"study_design_scores_gemma":[0.000168649,0.001197571,0.01426635,0.3390345,0.002298741,0.001667365,0.1042597,0.001952349,0.006855002,0.05232064,0.4757771,0.0002020939],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09530991,0.7649448,0.06535534,0.02671244,0.002217386,0.003119891,0.0005293054,0.0003592286,0.04145169],"genre_scores_gemma":[0.4572558,0.4324023,0.09218775,0.007618403,0.0006335634,0.004005199,0.0004745461,0.0001580801,0.005264426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03477191,"threshold_uncertainty_score":0.1838936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09306372714186048,"score_gpt":0.4289598083364948,"score_spread":0.3358960811946343,"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."}}