{"id":"W4220841160","doi":"10.2196/33934","title":"Leveraging Machine Learning to Understand How Emotions Influence Equity Related Education: Quasi-Experimental Study","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Academic Medical Organization of Southwestern Ontario","keywords":"Sentiment analysis; Population; Social media; Psychology; Equity (law); Computer science; Social psychology; Artificial intelligence; Political science; Medicine; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002397653,0.0001506511,0.0001935976,0.0002720576,0.002970467,0.0001335389,0.0005030617,0.0001107562,0.003001552],"category_scores_gemma":[0.007400351,0.0001834146,0.00004967258,0.00154186,0.0001729202,0.0003237744,0.0002201504,0.000833564,0.0000515135],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003058972,"about_ca_system_score_gemma":0.01261873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007976343,"about_ca_topic_score_gemma":0.0006857019,"domain_scores_codex":[0.9953759,0.001473151,0.0003800632,0.000452318,0.001873626,0.0004448882],"domain_scores_gemma":[0.9979635,0.0005544698,0.0002136532,0.0002487501,0.0002190671,0.0008005275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003071125,0.01266335,0.06147024,0.00002744617,0.00001970886,0.000001363668,0.8653439,0.00004531682,0.00002303207,0.006887588,0.006230317,0.04725697],"study_design_scores_gemma":[0.0003487983,0.0008857787,0.04635422,0.00004822961,0.00001772183,0.000005415631,0.8722751,0.00008711742,0.000004760249,0.001026446,0.07868143,0.0002650465],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9171247,0.0002916446,0.00002904794,0.06820929,0.008889176,0.002878614,0.000001369911,0.0001714176,0.002404736],"genre_scores_gemma":[0.9919921,0.0000174175,0.0001179628,0.001847667,0.0009114217,0.003814574,0.00005575407,0.00002423707,0.001218872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07486739,"threshold_uncertainty_score":0.9986296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08095600913243678,"score_gpt":0.4631642513418503,"score_spread":0.3822082422094135,"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."}}