{"id":"W4401044282","doi":"10.18653/v1/2024.starsem-1.2","title":"How Does Stereotype Content Differ across Data Sources?","year":2024,"lang":"en","type":"article","venue":"","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Content (measure theory); Stereotype (UML); Mathematics","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":[0.07896243,0.0009873976,0.001354698,0.01948337,0.001726448,0.008590565,0.001484649,0.001822126,0.002117879],"category_scores_gemma":[0.3455163,0.0009407381,0.001985153,0.01602114,0.003508406,0.009721018,0.006104131,0.001562357,0.001340477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001770692,"about_ca_system_score_gemma":0.001376592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004435913,"about_ca_topic_score_gemma":0.003605004,"domain_scores_codex":[0.8757452,0.0573447,0.01626691,0.01742809,0.03065605,0.002558919],"domain_scores_gemma":[0.5016963,0.3751357,0.03543244,0.04915049,0.03687106,0.001713948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004279728,0.0002116407,0.8469212,0.003099587,0.003913769,0.0003480001,0.02071748,0.001431207,0.004380913,0.005542904,0.01043104,0.1025743],"study_design_scores_gemma":[0.00009126082,0.0001570518,0.9077814,0.002039231,0.001232565,0.0009995531,0.01932484,0.00661166,0.00533767,0.02577017,0.03035115,0.0003034558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8466625,0.005757344,0.07461332,0.006167747,0.0009432702,0.001467737,0.03433446,0.001501081,0.02855245],"genre_scores_gemma":[0.948078,0.0009916535,0.01937158,0.001568283,0.0004417471,0.0008069986,0.02733668,0.0006071568,0.0007977797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07896243,"threshold_uncertainty_score":0.4175982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1965887360013194,"score_gpt":0.4187975240043027,"score_spread":0.2222087880029833,"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."}}