{"id":"W4294805199","doi":"10.5206/mt.v2i1.15198","title":"Another Famous Unsolved Problem: Improving Diversity in STEM","year":2022,"lang":"en","type":"article","venue":"Maple Transactions","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversity (politics); Computer science; Sociology; Anthropology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01476689,0.0007667124,0.0009568129,0.001693778,0.006520411,0.006393841,0.002327278,0.005271806,0.01866605],"category_scores_gemma":[0.047047,0.0002586727,0.0006367126,0.003495597,0.004919982,0.01329637,0.007399297,0.009926132,0.003169963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003602773,"about_ca_system_score_gemma":0.006180123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004934702,"about_ca_topic_score_gemma":0.00694087,"domain_scores_codex":[0.9931592,0.002993497,0.0001538964,0.000811126,0.002159523,0.000722797],"domain_scores_gemma":[0.9708214,0.01546909,0.00071489,0.002238989,0.007583106,0.003172461],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001766813,0.0002604349,0.002202624,0.0005963411,0.00008644816,0.00007086607,0.001694601,0.001870484,0.001523336,0.214661,0.4580653,0.3187918],"study_design_scores_gemma":[0.0001500541,0.0002499036,0.005279938,0.0006593842,0.00008153315,0.000170246,0.003223762,0.002892265,0.004303276,0.4292272,0.5536691,0.00009338626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01750132,0.02340043,0.03817971,0.8252209,0.01011899,0.00009997855,0.0006890091,0.0004302684,0.08435933],"genre_scores_gemma":[0.5375275,0.03804136,0.08295104,0.2265314,0.01942422,0.0005439136,0.001371535,0.001159131,0.09244987],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9852331,"threshold_uncertainty_score":0.07809567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04466521906081886,"score_gpt":0.2343465572530974,"score_spread":0.1896813381922785,"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."}}