{"id":"W4411142590","doi":"10.1145/3730408","title":"Humor for Graduate Training","year":2025,"lang":"en","type":"article","venue":"ACM Inroads","topic":"Humor Studies and Applications","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Institut de Valorisation des Données","keywords":"Training (meteorology); Graduate students; Medical education; Psychology; Computer science; Mathematics education; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001083556,0.00007185581,0.0001224638,0.00003966706,0.0001788309,0.00001089686,0.0002356533,0.00003382166,0.0001637955],"category_scores_gemma":[0.0001091195,0.00006483218,0.00006426228,0.000138482,0.00004065847,0.000007588942,0.00006310776,0.0000670567,0.0001259995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001057279,"about_ca_system_score_gemma":0.00001456098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003165254,"about_ca_topic_score_gemma":0.00001533073,"domain_scores_codex":[0.9994346,0.00001068668,0.0001293777,0.000183013,0.00003756396,0.000204754],"domain_scores_gemma":[0.999315,0.0001853617,0.00002764905,0.0004253658,0.00002360668,0.0000229893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000154612,0.00008452256,0.001844397,0.00001009578,0.0001701647,0.000001270865,0.008117884,8.617801e-7,0.0002157635,0.6357901,0.2428728,0.1108768],"study_design_scores_gemma":[0.0008171549,0.00005166101,0.07073861,0.00001110064,0.00004737796,0.000001360462,0.008336639,0.00001549858,0.0001092658,0.04110124,0.8786286,0.0001415182],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4758792,0.000313234,0.004108261,0.02784525,0.00142551,0.000795442,0.00005211324,0.0002180558,0.489363],"genre_scores_gemma":[0.9772518,0.00000481749,0.001732457,0.001417783,0.00009171156,0.0007788745,0.00001000984,0.000009182668,0.01870338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6357558,"threshold_uncertainty_score":0.264378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2224154136893508,"score_gpt":0.4548898234489757,"score_spread":0.2324744097596249,"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."}}